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The purpose of this paper is to understand the effect of online cross-recommendation of products from e-retailers on consumers’ instant cross-buying intention, and compare the effect between the contexts that the decision making on focal product is difficult and easy.

Based on the information adoption model, this paper develops a theoretical model to investigate how online cross-recommendation of products from e-retailers influence consumers’ instant cross-buying intention. Empirical data were collected from 224 online shoppers. The Partial Least Squares technique was used to test the proposed research model.

Choice confidence on focal product and perceived usefulness of cross-buying is the antecedents of instant cross-buying intention. Brand awareness of recommended product, one-stop shopping convenience, and perceived price advantage are the antecedents of perceived usefulness of cross-buying and choice confidence on focal product when the decision making on focal product is difficult, whereas brand awareness is not when it is easy to make focal product decision. Choice confidence on focal product positively affects perceived usefulness of cross-buying when it is easy to make focal product decision, whereas the effect is not significant when the decision making on focal product is difficult.

Knowledge about the effect of online cross-recommendation of products on instant cross-buying intention is scarce. This study reveals the psychological mechanism of the effect of online cross-recommendation of products on consumers’ instant cross-buying intention and finds that decision-making difficulty on focal product is an important moderator.

The purpose of this research is to study the influence of self-service technologies (SST) on cross-buying and word-of-mouth. This study tests the direct impact of perceived usefulness and perceived ease of use on cross-buying and word-of-mouth. Further, this study also tests the mediating role of e-service quality for the aforementioned relationships. The study has been undertaken in the context of retail banking in an emerging market, India.

A cross-sectional survey research design was used to collect data from 235 customers of retail banks in India. The data were analysed using IBM AMOS 23.0 taking structural equation modelling (SEM) approach to test the hypothesised relationships.

The findings of the study suggest that both perceived usefulness and perceived ease of use influence cross-buying and word-of-mouth. E-service quality partially mediates the relationship between perceived usefulness on cross-buying and word-of-mouth. E-service quality partially mediates the relationship between perceived ease of use and cross-buying but does not mediate the relationship between perceived ease of use and word-of-mouth.

This study shows that managers need to focus on perceived usefulness and perceived ease of use in order to ensure cross-buying and promote word-of-mouth recommendations by customers. Also, managers will be able to enhance cross-buying and promote word-of-mouth recommendations if e-service quality delivered by the bank is perceived to be good by customers.

This study contributes to the literature on SST and offers empirical evidence to show that perceived usefulness and perceived ease of use can influence cross-buying as well as word-of-mouth. Previous studies have shown that SST usage can foster loyalty, and the present study offers new evidence on the outcomes of behavioural loyalty. The study has been undertaken through responses taken from retail bank customers in an emerging market. This study also contributes to the literature on SST by testing the mediating effect of e-service quality for the above-mentioned relationships.

Many online merchants today have adopted web personalization in the form of personalized product recommendations (PPRs) to improve consumer’s decision quality. The purpose of this paper is to reveal the roles of PPRs on consumer decision quality in online shopping from the theoretical perspective of information load.

To explore the dual roles of PPRs on consumer decision quality, this paper develops a research model for it. A 2 (information load: high vs low) × 2 (web personalization: PPRs vs non-PPRs) between-subjects design is conducted to empirically test the model.

The results indicate that: first, information load can increase perceived information overload and decrease perceived information underload; second, PPRs can weaken (enhance) the positive (negative) effect of information load on perceived information overload (perceived information underload); third, both perceived information overload and perceived information underload are negatively associated with consumer’s decision quality.

This paper originally develops a research model that explains the roles of PPRs on consumer decision quality from the theoretical perspective of information load in the online shopping context, which could add new insights to the field of web personalization, especially the impact of web personalization on consumer decision making.

Although digitalization in the workplace is burgeoning, tools are needed to facilitate personalized learning in informal learning settings. Existing knowledge recommendation techniques do not account for dynamic and task-oriented user preferences. The purpose of this paper is to propose a new design of a knowledge recommender system (RS) to fill this research gap and provide guidance for practitioners on how to enhance the effectiveness of workplace learning.

This study employs the design science research approach. A novel hybrid knowledge recommendation technique is proposed. An experiment was carried out in a case company to demonstrate the effectiveness of the proposed system design. Quantitative data were collected to investigate the influence of personalized knowledge service on users’ learning attitude.

The proposed personalized knowledge RS obtained satisfactory user feedback. The results also show that providing personalized knowledge service can positively influence users’ perceived usefulness of learning.

This research highlights the importance of providing digital support for workplace learners. The proposed new knowledge recommendation technique would be useful for practitioners and developers to harness information technology to facilitate workplace learning and effect organization learning strategies.

This study expands the scope of research on RS and workplace learning. This research also draws scholarly attention to the effective utilization of digital techniques, such as a RS, to support user decision making in the workplace.

Prior literature indicates conflicting effects of online product information, which may complicate or simplify consumer purchase decisions. Therefore, the purpose of this paper is to investigate how different online product information (i.e. the choice set size and the popularity information and its presentation) affect consumers’ decision making and the related market outcomes.

This research relies on information-processing theories and social learning theory. By stepwise conducting two 2×2 within-subject factorial design experiments, this research examines the effects of the choice set size, product popularity information and product presentation on consumers’ decision making and the aggregated market outcomes.

The results show that product popularity information led consumers to either simplify or complicate their decision strategy, depending on the size of the choice sets. Additionally, presenting products by their popularity in descending order resulted in consumers making decisions with a larger decision bias. The results also show that the presence of product popularity was more likely to forge a “superstar” structure in a large market.

The research suggests that e-retailers and e-marketplace operators should carefully utilize product popularity information. Multiple mechanisms that shape different shopping environments with different orders are necessary to create a long-tailed market structure.

This study found the mixed effects of product popularity information when it is presented in different environments (i.e. the large/small choice set and the sorted/randomized product presentation). The overuse of popularity information may induce consumers’ decision bias.

The purpose of this study is to investigate consumers' emotional responses to artificial intelligence (AI) defeating people. Meanwhile, the authors investigate the negative spillover effect of AI defeating people on consumers' attitudes toward AI companies. The authors also try to alleviate this spillover effect.

Using four studies to test the hypotheses. In Study 1, the authors use the fine-tuned Bidirectional Encoder Representations from the Transformers algorithm to run a sentiment analysis to investigate how AI defeating people influences consumers' emotions. In Studies 2 to 4, the authors test the effect of AI defeating people on consumers' attitudes, the mediating effect of negative emotions and the moderating effect of different intentions.

The authors find that AI defeating people increases consumers' negative emotions. In terms of downstream consequences, AI defeating people induces a spillover effect on consumers' unfavorable attitudes toward AI companies. Emphasizing the intention of helping people can effectively mitigate this negative spillover effect.

The authors' findings remind governments, policymakers and AI companies to pay attention to the negative effect of AI defeating people and take reasonable steps to alleviate this negative effect. The authors help consumers rationally understand this phenomenon and correctly control and reduce unnecessary negative emotions in the AI era.

This paper is the first study to examine the adverse effects of AI defeating humans. The authors contribute to research on the dark side of AI, the outcomes of competition matches and the method to analyze emotions in user-generated content (UGC).

The purpose of this paper is to explore the effects of online recommender systems (RS) on three types of diversity: algorithmic recommendation diversity, perceived recommendation diversity and sales diversity. The analysis distinguishes different recommendation algorithms and shows whether user perceptions match the actual effects of RS on sales.

An online experiment was conducted using a realistic shop design, various recommendation algorithms and a representative consumer sample to ensure the generalizability of the findings.

Recommendation algorithms show a differential impact on sales diversity, but only collaborative filtering can lead to higher sales diversity. However, some of these effects are subject to how much information firms have about users’ preferences. The level of recommendation diversity perceived by users does not always reflect the factual diversity effects.

Recommendation and consumption patterns might differ for other types of products; future studies should replicate the study with search or credence goods. The authors also recommend that future research should move from taking a unidimensional measure for the assessment of diversity and employ multidimensional measures instead.

Online shops need to conduct a more comprehensive assessment of their RS’ effect on diversity, taking into account not only the effects on their sales distribution, but also on users’ perceptions and faith in the recommendation algorithm.

This study offers a framework for assessing different forms of diversity in online RS. It employs various recommendation algorithms and compares their impact using not just one but three different types of diversity measures. This helps explaining some of the contradictious findings from the previous literature.

There is an on-going debate about the role of workplace internet leisure (WIL) and whether it is a vice or virtue. Considering this, the purpose of this paper is to examine the effect of WIL on workplace outcome variables such as employee satisfaction (ES) and employee productivity in the Malaysian context.

Data were collected using a self-administered questionnaire that yielded 282 responses. Partial least square technique using SmartPLS-3 was used to test the study hypotheses.

Findings reveal that workplace WIL, workplace WIL policy and workplace autonomy orientation (WAO) affect employees’ satisfaction. Additionally, the mediating role of ES was found to be significant.

The findings of this study are valuable for both managers and policy makers. These results can benefit the managers of conventional banks in Malaysia to decide how to enhance employees’ satisfaction and productivity by focusing on the key drivers such as WIL, workplace internet leisure policy (WILP) and WAO.

This is a pioneering study which suggests that moderate use of WIL can have a positive and significant effect on workplace outcome variables. Moreover, this study theorised ES as a mediating variable; this helps to explain how organisations can transform workplace resources in term of internet leisure, WILP and WAO into high productivity by elevating employees’ satisfaction.

Previous research about online recommendation systems has focused largely on their impact on customers' purchase decisions regarding the products being recommended, but it has mostly ignored how they may affect focal product evaluation. This research aimed to examine the influence of recommendation type (i.e. substitute-based vs complement-based) on focal product evaluation dependent on the brand image (i.e. warm vs competent).

Four laboratory experiments were conducted. Study 1 adopted an implicit association task. Studies 2 and 3 used a 2 (image: warmth vs competence) × 2 (product display: complements vs substitutes) between-subjects experimental design. Study 4 used a 2 (decision stage) × 2 (image) × 2 (product display) × continuous (need for cognition) between-subjects design.

Study 1 demonstrated a general “complementation (competition)—warmth (competence)” association. Studies 2 and 3 found that when a focal product had a warm (competent) image, complement-based (substitute-based) recommendations led customers to evaluate it more favorably than substitute-based (complement-based) recommendations. Study 3 further demonstrated that processing fluency mediates the above effect. Study 4 showed that this effect relies on heuristic processing and disappears for those who are in the screening stage or have a high need for cognition.

Theoretically, this research extends the understanding of the stereotype content model of focal product brand image, the feelings-as-information process, and moderating roles of processing stage and need for cognition in e-commerce contexts. Practically, the findings provide online retailers a guideline for customizing their recommendation systems.

Collaborative filtering based recommender systems (CF–RS) are widely used to recommend products based on consumers' preference similarity. Recommendations by CF–RS merely provide suggestions as “people who bought this also bought this” while, consumers are unaware about the source of these recommendations. By amalgamating CF–RS with consumers' social network information, e-commerce sites can offer recommendation from social networks of consumers. These social network embedded systems are known as social recommender systems (SRS). The extant literature has researched on the algorithms and implementation of these systems; however, SRS have not been understood from consumers' psychological perspective. This study aims to qualitatively explore consumers' motives to accept SRS in e-commerce websites.

This qualitative study is based on in-depth interviews of frequent online shoppers. SRS are currently not very widespread in the Indian e-commerce space; hence, a vignette was shown to respondents before they responded to the questions. Inductive qualitative content analysis method was used to analyse these interviews.

Three main themes (social-gratification, self-gratification and information-gratification) emerged from the analysis. Out of these, social-gratification acts as an enabler, while self-gratification along with some elements of information-gratification act as inhibitors towards acceptance of social recommendations. Based on these gratifications, we present a conceptual model on consumer's acceptance of social recommendations.

This study is an initial attempt to qualitatively understand consumers' attitudes and acceptance of social recommendations on e-commerce websites, which in itself is a fairly new phenomenon.