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The purpose of this study is to examine the effect of perceived value of recommended product on consumer’s e-loyalty, based on the proposition of expectation confirmation theory. Vendors’ reputation is tested as the mediator in the perceived value of recommended product and e-loyalty relationship, whereas shopping enjoyment is predicted as the moderator that conditions the perceived value of recommended product and e-loyalty relationship through vendors reputation.

Data were collected via an online survey platform and through a QR code. Partial least squares analysis, confirmatory factor analysis and structural equation modeling were used to verify the research proposed model.

The findings revealed that the perceived value of recommended product had a significant positive effect on E-loyalty; in addition, the perceived value of the recommended product and e-loyalty link was partly explained by e-shopper’s confidence in vendor reputation. Therefore, the study established that the direct and indirect relationship between the perceived value of the recommended product and e-loyalty was sensitive and profound to shopping enjoyment.

This study has established that the perceived value of a recommended product can result in consumer loyalty. This has successively provided the e-shop manager and other stakeholders with novel perspectives about why it is necessary to understand consumers’ pre- and postacquisition behavior before recommending certain products to the consumer.

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.

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.

The purpose of this paper is to offer a novel perspective on resale pricing in franchising, i.e. from a franchisee perspective, by combining legal and managerial considerations in the European context. The objective is to assess franchisee perceptions regarding resale pricing in their chains.

The authors adopt a qualitative approach and use 46 in-depth interviews with franchisees covering retail and service industries in the French market.

Many of the interviewed franchisees believe that joining a franchise chain involves respecting the recommended resale prices. For some of the franchisees, in link with the chain uniformity, imposing uniform resale prices throughout the chain represents a strength, because customers who visit different stores within the franchise chain expect to find consistent pricing. Moreover, many franchisees consider that their franchisors have some know-how that they use to set correct resale prices, taking into account the profit margin.

This research contributes to the literature on resale pricing in franchising, as well as the franchising literature in general, by combining legal and managerial considerations, adopting a franchisee perspective, covering retail and service industries and focusing on French and European markets.

This research can be viewed by franchise experts, franchisors, franchisees and franchisee candidates as a synthesis of resale price-related legal aspects, adopted practices and potential conflicts in franchise chains in the French market. It also highlights price-related practices to be avoided to prevent potential conflicts.

The subject of resale pricing in franchise chains is a hot topic, because of its link with customer attraction, chain uniformity, franchisor know-how, franchisee autonomy and the legal dimension.

The purpose of this paper is to improve the customer satisfaction by offering online personalized recommendation system.

By employing an innovative associative classification method, this paper is able to predict a customer’s pleasure during the online while-recommending process. Consumers can make an active decision to recommended products. Based on customer’s characteristics, a product will be recommended to the potential buyer if the model predicts that he/she will click to view the product. That is, he/she is satisfied with the recommended product. Finally, the feasibility of the proposed recommendation system is validated through a Taobao shop.

The results of the experimental study clearly show that the online personalized recommendation system maximizes the customer’s satisfaction during the online while-recommending process based on an innovative associative classification method on the basis of consumer initiative decision.

Conventionally, customers are considered as passive recipients of the recommendation system. However, customers are tired of the recommendation system, and they can do nothing sometimes. This paper designs a new recommendation system on the basis of consumer initiative decision. The proposed recommendation system maximizes the customer’s satisfaction during the online while-recommending process.

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.

This paper investigates the effects of advising strength of a recommendation agent on users' trust and distrust beliefs and how the effects are moderated by perceived brand familiarity.

A research model is evaluated using a laboratory experiment with 149 participants.

Results reveal that a strong advising tone leads to higher trust in terms of users' credibility and benevolence beliefs and lower distrust in terms of their discredibility beliefs (the trustor's concerns regarding the trustee's dishonesty and competence in engaging in harmful behavior) when perceived brand familiarity is high. By contrast, when brand familiarity is low, strong advising tone results in low trust in terms of users' credibility belief and high distrust in terms of their beliefs in discredibility and malevolence (concerns regarding the trustee's conduct in terms of a malicious intention that can hurt the trustor's welfare).

This paper contributes to the trust and distrust literature by studying how each of the dimensions of trust and distrust can be affected by an RA's design feature. It extends the attribution theory to the RA context by studying the moderating role of brand familiarity in determining the effects of the advising strength of an RA. It provides actionable guidelines for practitioners regarding the adoption of an RA's appropriate advising strength to promote different types of products.

Recommender system approaches such as collaborative and content-based filtering rely on user ratings and product descriptions to recommend products. More recently, recommender system research has focussed on exploiting knowledge from user-generated content such as product reviews to enhance recommendation performance. The purpose of this paper is to show that the performance of a recommender system can be enhanced by integrating explicit knowledge extracted from product reviews with implicit knowledge extracted from analysis of consumer’s purchase behaviour.

The authors introduce a sentiment and preference-guided strategy for product recommendation by integrating not only explicit, user-generated and sentiment-rich content but also implicit knowledge gleaned from users’ product purchase preferences. Integration of both of these knowledge sources helps to model sentiment over a set of product aspects. The authors show how established dimensionality reduction and feature weighting approaches from text classification can be adopted to weight and select an optimal subset of aspects for recommendation tasks. The authors compare the proposed approach against several baseline methods as well as the state-of-the-art better method, which recommends products that are superior to a query product.

Evaluation results from seven different product categories show that aspect weighting and selection significantly improves state-of-the-art recommendation approaches.

The proposed approach recommends products by analysing user sentiment on product aspects. Therefore, the proposed approach can be used to develop recommender systems that can explain to users why a product is recommended. This is achieved by presenting an analysis of sentiment distribution over individual aspects that describe a given product.

This paper describes a novel approach to integrate consumer purchase behaviour analysis and aspect-level sentiment analysis to enhance recommendation. In particular, the authors introduce the idea of aspect weighting and selection to help users identify better products. Furthermore, the authors demonstrate the practical benefits of this approach on a variety of product categories and compare the approach with the current state-of-the-art approaches.

The purpose of this paper is to provide of selected Financial Industry Regulatory Authority (FINRA) regulatory notices and disciplinary actions issued in January, February, and March 2012.

The paper provides Regulatory Notice 12‐03, January 2012, Complex Products: Heightened Supervision of Complex Products; Regulatory Notice 12‐05, January 2012, Customer Account Protection: Verification of Emailed Instructions to Transmit or Withdraw Assets from Customer Accounts; Regulatory Notice 12‐13, March 2012, Best Execution, SEC Approves Consolidated FINRA Best Execution Rule. It summarizes ten disciplinary actions for recommending unsuitable sales of unit investment trusts (UITs) and floating rate loan funds; using misleading marketing materials in the sale of a non‐traded real estate investment trust (REIT); selling interests in private placement offerings without having a reasonable basis for recommending the securities; unsuitable sales of reverse convertible securities; violating Regulation SHO (Reg SHO) and failing to properly supervise short sales of securities and marking of sale orders; misrepresenting delinquency data and inadequate supervision in connection with the issuance of residential subprime mortgage securitizations (RMBS); permitting a registered representative to publish advertisements that failed to provide a sound basis for a reader to evaluate the products and services being offered, contained exaggerated, unwarranted and misleading statements, and failed to disclose the firm's name; failing to conduct reasonable due diligence regarding securities an entity issued; failing to disclose certain conflicts of interest in research reports and research analysts' public appearances; and failing to develop and enforce written procedures reasonably designed to achieve compliance with NASD Rule 3010(d)(2) regarding the review of electronic correspondence.

The paper reveals for Regulatory Notice 12‐03 that the decision to recommend complex products to retail investors is one that a firm should make only after the firm has implemented heightened supervisory and compliance procedures; firms also should monitor the sale of these products in a manner that is reasonably designed to ensure that each product is recommended only to a customer who understands the essential features of the product and for whom the product is suitable. For Notice 12‐05 it finds that, given the rise in incidents reported to FINRA involving fraud perpetrated through compromised customer e‐mail accounts, FINRA recommends that firms reassess their specific policies and procedures for accepting and verifying instructions to withdraw or transfer customer funds that are transmitted via email or other electronic means, as well as firms' overall policies and procedures in this area. For Notice 12‐13: FINRA Rule 5310 leaves in place the general requirements of best execution, which are for a member firm, in any transaction for or with a customer or a customer of another broker‐dealer, to use “reasonable diligence” to ascertain the best market for a security and to buy or sell in such market so that the resultant price to the customer is as favorable as possible under prevailing market conditions.

These are direct excerpts designed to provide a useful digest for the reader and an indication of regulatory trends.

This study aims to explore the opposite effects of single-category versus multi-category products information diversity on consumer decision making. Further, the authors investigate the moderating role of three categories of visitors – direct, hesitant and hedonic – in the relationship between product information diversity and consumer decision making.

The research utilizes a sample of 1,101,062 product click streams from 4,200 consumers. Visitors are clustered using the k-means algorithm. The diversity of information recommendations for single and multi-category products is characterized using granularity and dispersion, respectively. Empirical analysis is conducted to examine their influence on the two-stage decision-making process of heterogeneous online visitors.

The study reveals that the impact of recommended information diversity on consumer decision making differs significantly between single-category and multiple-category products. Specifically, information diversity in single-category products enhances consumers' click and purchase intention, while information diversity in multiple-category products reduces consumers' click and purchase intention. Moreover, based on the analysis of online visiting heterogeneity, hesitant, direct and hedonic features enhance the positive impact of granularity on consumer decision making; while direct features exacerbate the negative impact of dispersion on consumer decision making.

First, the article provides support for studies related to information cocoon. Second, the research contributes evidence to support the information overload theory. Third, the research enriches the field of precision marketing theory.