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The roles recommendation systems play in health care have become crucial in achieving effective care and in meeting the needs of modern care giving. As a result, efforts have been geared toward using recommendation systems in the management of chronic diseases. Effectiveness of these systems is determined by evaluation following implementation and before deployment, using certain metrics and criteria. The purpose of this study is to ascertain whether consideration of criteria during the design of a recommendation system can increase acceptance and usefulness of the recommendation system.

Using survey-style requirements gathering method, the specific health and technology needs of people living with chronic diseases were gathered. The result was analyzed using quantitative method. Sets of harmonized criteria and metrics were used along with requirements gathered from stakeholders to establish relationship among the criteria and the requirements. A matching matrix was used to isolate requirements for prioritization. These requirements were used in the design of a mobile app.

Matching criteria against requirements highlights three possible matches, namely, exact, inferential and zero matches. In any of these matches, no requirement was discarded. This allows priority features of the system to be isolated and accorded high priority during the design. This study highlights the possibility of increasing the acceptance rate and usefulness of a recommendation system by using metrics and criteria as a guide during the design process of recommendation systems in health care. This approach was applied in the design of a mobile app called Recommendations Sharing Community for Aged and Chronically Ill People. The result has shown that with this method, it is possible to increase acceptance rate, robustness and usefulness of the product.

Inability to know the evaluation criteria beforehand, inability to do functional analysis of requirements, lack of well-defined requirements and often poor cooperation from people living with chronic diseases during requirements gathering for fear of stigmatization, confidentiality and privacy breaches are possible limitations to this study.

The result has shown that with this method, it is possible to isolate more important features of the system and use them during the design process, thereby speeding up the design and increasing acceptance rate, robustness and usefulness of the system. It also helps to see in advance the likely features of the system that will enhance its usefulness and acceptance, thereby increasing the confidence of the developers in their ability to deliver a system that will meet users’ needs. As a result, developers know beforehand where to concentrate their efforts during system development to ascertain the possibility of increasing usefulness and acceptance rate of a recommendation system. In addition, it will also save time and cost.

This paper demonstrates originality by highlighting and testing the possibility of using evaluation criteria and metrics during the design of a recommender system with a view to increasing acceptance and enhancing usefulness. It also shows the possibility of using the metrics and criteria in system’s development process for an exercise other than evaluation.

The purpose of this study is to investigate how book group recommendations can be used as a meaningful way to suggest suitable books to users, given the increasing number of individuals engaging in sharing and discussing books on the web.

The authors propose reviews fine-grained classification (CFGC) and its related models such as CFGC1 for book group recommendation. These models can categorize reviews successively by function and role. Constructing the BERT-BiLSTM model to classify the reviews by function. The frequency characteristics of the reviews are mined by word frequency analysis, and the relationship between reviews and total book score is mined by correlation analysis. Then, the reviews are classified into three roles: celebrity, general and passerby. Finally, the authors can form user groups, mine group features and combine group features with book fine-grained ratings to make book group recommendations.

Overall, the best recommendations are made by Synopsis comments, with the accuracy, recall, F-value and Hellinger distance of 52.9%, 60.0%, 56.3% and 0.163, respectively. The F1 index of the recommendations based on the author and the writing comments is improved by 2.5% and 0.4%, respectively, compared to the Synopsis comments.

Previous studies on book recommendation often recommend relevant books for users by mining the similarity between books, so the set of book recommendations recommended to users, especially to groups, always focuses on the few types. The proposed method can effectively ensure the diversity of recommendations by mining users’ tendency to different review attributes of books and recommending books for the groups. In addition, this study also investigates which types of reviews should be used to make book recommendations when targeting groups with specific tendencies.

In the aftermath of the 2021 Financial Action Task Force Mutual Evaluation Report, legislators, supervisory bodies, law enforcement and the like are focusing on preventing South Africa from being greylisted. This paper performs an analysis of the 2021 South African Financial Action Task Force (FATF) Mutual Evaluation, specifically Recommendation 8 and Immediate Outcome 10. The purpose of this paper is to address the concerns raised and assist those tasked with implementing remediation measures.

Secondary sources such as legislation, case law, textbooks and peer-reviewed publications are used in addressing the concerns. A major focus is placed on the evaluation itself, with an analysis of Recommendation 8 and Immediate Outcome 10.

Despite the non-compliance rating and a low level of effectiveness received regarding non-profit organisations, authorities might not place a large focus on remediating this, as more pertinent issues arise in the report. The lack of focus in this area adds to the likelihood of grey listing by FATF. However, with co-operation from the relevant stakeholders, these low ratings can be improved.

Since the Mutual Evaluation’s release in October 2021 there have not been any papers addressing the highlighted issues in the non-profit sector in South Africa, to the best of the authors’ knowledge. This paper will be the first of its kind and will be of use to authorities as regards mitigating the concerns raised by FATF.

This paper aims to provide a detailed case study of a corporate foresight for innovation (CFI) project done by the Higher School of Economics’ (HSE) (Moscow, Russia) corporate foresight (CF) unit for a large state-owned Russian service company. It demonstrates how CFI methods lead to recommendations and how these recommendations result in decisions.

Drawing from being part of the project team, review of the project documents and interviews, the case describes a multi-phased CFI project which incorporated several CF methods. Techniques used for the project itself included grand challenges and trend analysis, analysis of best practices through use of benchmarking and horizon scanning, interviews, expert panels, wild card and weak signals analysis, cross impact analysis, SWOT and backcasting. The project used a broad-base of secondary information, expert panels consisting of company experts and HSE CF team personnel, interviews with senior management and an extensive literature review using HSE’s propriety iFORA system.

In all 17 CFI recommendation and over 100 implementation recommendations were made; 94 per cent of the CFI recommendations were accepted with most implemented at the time this case was written. The case also identifies five enabling factors that collectively both helped the CFI project and led to a high rate of recommendation acceptance and one factor that hindered CFI project success.

The case study provides detailed information and insight that can help others in conducting CF for innovation projects and establishes a link between CF methods and innovation-based recommendations and subsequent decisions.

In-depth case studies that show academe and practitioners how CFI leads to recommendations and is linked to subsequent decisions have been identified as a gap in the literature. This paper therefore seeks to address this need by presenting a detailed CF case for a corporate innovation project.

The TESOL (teaching of English to speakers of other languages) sector in New Zealand is rapidly developing into a major educational service industry. Despite their growing national importance, little is known about the performance of the English language centres (ELCs) that constitute the industry. This study investigated levels of client satisfaction with New Zealand ELC service at a national level. The research took a services management approach, using a multilingual questionnaire covering nine dimensions of ELC service. The findings indicated that, overall, clients registered mere satisfaction with the service provided. Statistical analysis identified significant differences between levels of client satisfaction in terms of client age and nationality and between ELCs of different type and size. While service provider personal attributes were positively rated by respondents, these did not play a major role as predictors of client satisfaction or the willingness to recommend an ELC.

The purpose of this paper is to provide a comprehensive review on electronic word-of-mouth (eWOM) credibility. Further, the authors propose a comprehensive and integrated model on eWOM credibility.

The authors conducted a systematic review of the extant literature on marketing, sociology and psychology to identify the factors that affect eWOM credibility. Further, the authors developed themes and identified factors which lead to eWOM credibility.

Four factors were identified, i.e. content, communicator, context and consumer, which affect eWOM credibility. Several variables associated with these four factors were identified, which result in eWOM credibility. Further, the authors developed 22 propositions to explain the causal relationship between these variables and eWOM credibility.

The conceptual model needs empirical validation across various eWOM platforms, i.e. social networking websites, e-commerce websites, etc.

Managers and e-commerce vendors can use these inputs to develop specific design elements and assessment tools which can help consumers to identify credible eWOM messages. Credible eWOM messages, in turn, will increase the “trust” and “loyalty” of the customers on e-commerce vendors.

This paper provides a conclusive takeaway of eWOM credibility literature by integrating multiple perspectives and arguments from the extant literature. This study also presents an integrated model, which provides a theoretical framework for researchers to further examine the interaction effect of various variables, which results in eWOM credibility.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-06-2020-0263

With the exponential growth of the amount of data, the most sophisticated systems of traditional libraries are not able to fulfill the demands of modern business and user needs. The purpose of this paper is to present the possibility of creating a Big Data smart library as an integral and enhanced part of the educational system that will improve user service and increase motivation in the continuous learning process through content-aware recommendations.

This paper presents an approach to the design of a Big Data system for collecting, analyzing, processing and visualizing data from different sources to a smart library specifically suitable for application in educational institutions.

As an integrated recommender system of the educational institution, the practical application of Big Data smart library meets the user needs and assists in finding personalized content from several sources, resulting in economic benefits for the institution and user long-term satisfaction.

The need for continuous education alters business processes in libraries with requirements to adopt new technologies, business demands, and interactions with users. To be able to engage in a new era of business in the Big Data environment, librarians need to modernize their infrastructure for data collection, data analysis, and data visualization.

A unique value of this paper is its perspective of the implementation of a Big Data solution for smart libraries as a part of a continuous learning process, with the aim to improve the results of library operations by integrating traditional systems with Big Data technology. The paper presents a Big Data smart library system that has the potential to create new values and data-driven decisions by incorporating multiple sources of differential data.

The recommendation of the analyst report is not only limited to a small number of ratings, but also biased toward a buy opinion with the absence of sell opinion. As an alternative to this, this paper aims to extract analysts' textual opinions embedded in the report body through text analysis and examine the profitability of investment strategies. Analyst opinion about a firm is measured by calculating the frequency of positive and negative words in the report text through the Korean sentiment lexicon for finance (KOSELF). To verify the usefulness of textual opinions, the author constructs a calendar-time based portfolios by the analysts' textual opinion variable of each stock. When opinion level is used, investment strategy has no significant hedged portfolio return. However, hedged portfolio constructed by opinion change shows significant return of 0.117% per day (2.57% per month). In addition, the hedged return increases to 0.163% per day (3.59% per month) when the opening price is used instead of closing price. This study show that the analysts’ opinion extracted from text analysis contains more detailed spectrum than recommendation and investment strategies using them give significant returns.

Owner‐managers of small businesses invariably cite word of mouth recommendations as the principal way in which they attract new customers. Marketing theory is under‐developed in this field with little empirical evidence about the recommending behaviour of small business customers and referral groups. The case study of an independent health club reported here illustrates how these processes can be researched and the results used to influence word of mouth recommendations. The owner‐manager of the club carried out some basic research on his customer base in order to identify the types of members who were most active in recommending the club, and the stimuli that led to recommendations being made. A key finding was that newer members were more likely to recommend than those who had been members for some time, contradicting the implications of relationship marketing theories that long standing customers generate most recommendations. Membership more than doubled following a number of activities designed to increase recommending behaviour. The most important stimuli to recommendations were believed to be involvement with the club, incentives and experiential factors. The case study indicates that word of mouth strategies benefit from research to find out which customers are recommending the business, what they are recommending about the business and what prompts them to do so.

I test empirically the hypothesis that the monitoring role of the board of directors depends on the severity of the agency problems and the amount of information needed to monitor. I show that in high growth firms, where the agency conflicts are low and managers are likely to reveal more information to get advice, boards are more independent but less likely to monitor, while in low growth firms, boards are less likely to be independent, but the relationship between firm value and board independence is strong. Overall, boards become more independent but monitor less as firms’ growth opportunities increase, suggesting that managers trade off the amount of information released to the board to get a better advice and to mitigate the monitoring role of the board.