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This study aims to investigate whether and to what extent the characteristics of headlines impact the attraction of online financial articles by using data collected from WeChat, a popular social app in China.

By integrating the methods of econometric and text mining, this study analyzed the content of 113,917 headlines published by 126 official accounts from the day account being created to May 12, 2016. Hierarchical regression was used to investigate the effects of headline features, account ownership type and stock market volatility on the attraction of online financial articles.

The empirical results show that sentiment, length, domain specificity and language intensity in a headline are significantly associated with the attraction of an online financial article. In addition, the relative and moderating roles of stock market volatility and account ownership type were also explored, showing significant moderating effects on the relationship between sentiment and online article attraction.

This study had several limitations. First, the sample data for this research were collected from one social media platform. While WeChat is the most popular social media application in China, it is just one of the many social media applications that can be used to publish online financial articles, and it differs from other social media applications greatly. This makes it hard to generalize the conclusions of the study. Future studies could compare the different features of headlines and their effects on the attraction of financial articles on different platforms. Second, in mining the characteristics of headline, this study only analyzed the influence of the sentiment, domain specificity, length and language intensity of the headline on article attraction. In future studies, in-depth analysis of the headline content could be conducted, such as the similarity between the body text and the headline, the theme and the sense of humor. However, the authors believe that these limitations do not have major negative implications for the results and contributions of this study.

From a practical perspective, this work could help official WeChat accounts to write better headlines for the articles they publish to attract more readers and fans and thus improve the value of their accounts, which would enable them to maximize the tangible benefits through differential pricing on advertisement placement.

The contributions of this study are as follows. First, the paper explored how headline sentiment influences article attraction and found that positive sentiment is negatively related to article attraction, while negative sentiment is positively related to article attraction. In addition, there is an inverted U-shaped relationship between the extent of negative sentiment and article attraction. Second, the paper investigates how headline domain specificity affects article attraction and there is an inverted U-shaped relationship between headline domain specificity and article attraction. Third, to the best of the authors’ knowledge, this is the first large-scale case study that explores the association between stock market volatility and the attraction of an online financial article.

The purpose of this paper is to assess the validity of the Autism Diagnostic Interview-Revised (ADI-R) in an Iranian population to determine its efficacy in identifying children with autism spectrum disorder (ASD) who parents have Persian-speaking parents.

A case–control study was performed in March until July 2020 in Hamadan city, Iran. The case group was children were examined by the clinicians used a coding scheme based on the DSM-IV criteria for ASD. The control group was all children in the family, including healthy siblings, were asked to participate in the study. The reliability, content and face validity were performed to assess the psychometric properties of the tool. Confirmatory factor analysis (CFA) was performed to evaluate the four-dimensional structure of the tool (Scores A, B, C and D). Statistical analysis was performed using AMOS for SPSS 21, and the statistical significant level was less than 0.05.

The quantitative content validity analysis revealed that the mean of content validity ratio (CVR) and content validity index (CVI) for all domains was 0.94 and 0.91, respectively. For CFA, four domains A, B, C and D were used and demonstrated a good fit (CFI = 0.92 and RMSEA = 0.06). The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) in domains A, B (verbal), C and D were 100%. For domain B (non-verbal), the sensitivity, specificity, PPV and NPV were 86.7%, 100%, 100% and 88.2%, respectively.

This study showed that ADI-R has sufficient ability to discriminate between children with ASD and those with no psychiatric diagnosis, and it is a reliable tool in Iran. The sensitivity and specificity for correctly diagnosing ASD was high, regardless of the age and cognitive level of the examiner.

To the best of the authors’ knowledge, this is the first paper on psychometric properties of ADI-R in children with ASD.

In spite of the merits of artificial intelligence (AI) in marketing and social media, harm to consumers has prompted calls for AI auditing/certification. Understanding consumers’ approval of AI certification entities is vital for its effectiveness and companies’ choice of certification. This study aims to generate important insights into the consumer perspective of AI certifications and stimulate future research.

A literature and status-quo-driven search of the AI certification landscape identifies entities and related concepts. This study empirically explores consumer approval of the most discussed entities in four AI decision domains using an online experiment and outline a research agenda for AI certification in marketing/social media.

Trust in AI certification is complex. The empirical findings show that consumers seem to approve more of non-profit entities than for-profit entities, with the government approving the most.

The introduction of AI certification to marketing/social media contributes to work on consumer trust and AI acceptance and structures AI certification research from outside marketing to facilitate future research on AI certification for marketing/social media scholars.

For businesses, the authors provide a first insight into consumer preferences for AI-certifying entities, guiding the choice of which entity to use. For policymakers, this work guides their ongoing discussion on “who should certify AI” from a consumer perspective.

To the best of the authors’ knowledge, this work is the first to introduce the topic of AI certification to the marketing/social media literature, provide a novel guideline to scholars and offer the first set of empirical studies examining consumer approval of AI certifications.

Following the hierarchy-of-effects model, this study aims to propose a two-step process framework to investigate social media post efficacy via attraction and likes.

The study analyzes 113,785 social media posts from 126 WeChat official accounts to explore how external (headline features and account type) and internal (content features and media type) features impact social media post attractions and likes, respectively.

The antecedents of post attraction differ from those of post likes. First, headline features (punctuation, length, sentiment and lexical density) and account type significantly influence social media post attraction. Second, content features (depth, tone, domain specificity, lexical density and readability) and media type affect social media post likes.

First, this study considers online user engagement as a two-step process regarding social media posts and explores different influencing factors. Second, the study constructs new variables (account type and domain specificity) in each stage of the two-step process model.

“It is now becoming widely recognised that many of the central unresolved problems in economics turn on questions of knowledge” (Loasby, 1986, p. 41). Nearly twenty years after that was written, it may be appropriate to take a (necessarily selective) look at ideas about human knowledge and to suggest some implications for the practice of economists. The ideas with which we shall begin long predate the observation that I have just recalled; and the delay in recognising their implications indicates how the growth of knowledge is dependent on the formation of appropriate linkages – which of course are not recognised as appropriate until they have been formed. Adam Smith, Alfred Marshall and Friedrich Hayek were all confronted with the uncertain basis of knowledge before they began their study of economics; and what their responses have in common is not only a theoretical focus on the process by which people develop what we call “knowledge” but also a reliance on similar kinds of process, which result in the formation of connections within particular domains. Each author recognises the impossibility of demonstrating that any such process can deliver proven truth; instead each envisages sequences of trial and error within particular contexts, leading to the preservation of what seems to work – until it no longer does, when a new sequence of trial and error begins. In other words, they all offer evolutionary theories, Marshall and Hayek explicitly so, while Smith, directly and indirectly, had a major influence on the development of Darwin’s ideas.

Purpose – This chapter introduces two empirical models that could be used to examine the influence of Eastern and Western culture on strategic management: the cultural consensus model (CCM) and the cultural mixture model (CMM).

Methodology/approach – We describe how strategic management scholars can use these models and suggest areas where these models can be of greatest use, including international market entry, international mergers and acquisitions and international alliances, global headquarters and subsidiary relationships, and corporate governance.

Findings – Originally developed by cognitive anthropologists and cultural psychologists, these models can measure domain specificity, scope, and heterogeneity of cultural influences within and across Eastern and Western societies; can address multilevel issues; and can measure an individual or firm's representativeness of the culture.

Social implications – This new research methodology can help strategic management researchers address the impact of “West meets East” on strategic management outcomes and processes.

Originality/value of chapter – The two empirical models provide methodologies that integrate qualitative and quantitative methods.

The purpose of this paper is to investigate how a distributed network architecture, building on web‐service orchestration, data‐stream management systems and smart‐tagging technologies, can be employed to enable enterprise collaboration and decision making.

The methodology is based on a technology review in order to propose a network design as well as a field survey to identify and evaluate the relevance of radio frequency identification (RFID)‐enabled collaboration and decision‐support scenarios to industry executives.

The paper demonstrates the relevance of the proposed architecture and corresponding RFID‐enabled collaboration to business executives of the grocery retail sector. The responses show that some scenarios are more appealing to retailers than to suppliers and that certain processes should be done in collaboration.

Research limitations and future research directions involve the evaluation of specific design alternatives, in the specific context as well as comparing the distributed architecture approach with a centralized architecture or with EDI which has traditionally been used to support enterprise collaboration.

The proposed architecture supports not only internal operations of network leaders, such as big retailers, but also suppliers who look into opportunities to benefit from the use of IT in enterprise relationships by gaining either process specificity or domain knowledge specificity.

The paper introduces a novel architecture that moves beyond the centralized web site paradigm to a distributed one. A European field survey is employed for the evaluation of several RFID‐enabled collaboration scenarios, providing insights to both researchers and practitioners (retailers and suppliers in the grocery retail sector).

Guided by Bronfenbrenner’s Ecological System’s model, this study documented acculturation and parental involvement in low-income Chinese immigrant homes that serve as predictors of parental mediation. By surveying 165 parents of 3–13-year-old immigrant children, this study found that low-income Chinese parents enacted restrictive mediation the most and exhibited a slow acculturation process even after an average of seven years of emigration. Higher parental acculturation was related to a higher use of active and restrictive mediation. Additionally, different aspects of parental involvement also served as predictors of the three mediation strategies. Chinese cultural emphasis on academic excellence and success was used to help interpret the findings. Future research should consider implementing research-based adult media literacy programs for immigrant parents to help them practice their parental mediation skills in the host culture.

The purpose of this paper is to review the literature concerning supply chain management technology (SCMT) and financial performance, and to present a model for evaluating the financial performance benefits of investments in supply chain management technologies. The literature review and the associated model also lead to a discussion of opportunities for future research in the area.

To develop the model, a comprehensive review of the literature investigating the financial performance benefits of SCMT and other closely‐related information technologies, such as inter‐organizational systems, was performed. Findings from the reviewed studies were assimilated and used as the basis for the proposed model and for recommended avenues of future research.

The literature reviewed suggested that financial performance improvements from SCMT investments are derived from improvements in knowledge‐intensive capabilities, which lead to improvements in operational capabilities, leading, in turn, to first‐ and second‐order benefits. The ability to realize benefits is also influenced by a firm's position within the supply chain and exogenous economic forces.

This paper contributes to the knowledge of how financial gains are realized as the result of investments in SCMT, and provides context within which future research efforts can be placed. Future research opportunities are also discussed.

Large terminologies usually contain a mix of terms that are either generic or domain specific, which makes the use of the terminology itself a difficult task that may limit the positive effects of these systems. The purpose of this paper is to systematically evaluate the degree of domain specificity of the AGROVOC controlled vocabulary terms as a representative of a large terminology in the agricultural domain and discuss the generic/specific boundaries across its hierarchy.

A user-oriented study with domain-experts in conjunction with quantitative and systematic analysis. First an in-depth analysis of AGROVOC was carried out to make a proper selection of terms for the experiment. Then domain-experts were asked to classify the terms according to their domain specificity. An evaluation was conducted to analyse the domain-experts’ results. Finally, the resulting data set was automatically compared with the terms in SUMO, an upper ontology and MILO, a mid-level ontology; to analyse the coincidences.

Results show the existence of a high number of generic terms. The motivation for several of the unclear cases is also depicted. The automatic evaluation showed that there is not a direct way to assess the specificity degree of a term by using SUMO and MILO ontologies, however, it provided additional validation of the results gathered from the domain-experts.

The “domain-analysis” concept has long been discussed and it could be addressed from different perspectives. A resume of these perspectives and an explanation of the approach followed in this experiment is included in the background section.

The authors propose an approach to identify the domain specificity of terms in large domain-specific terminologies and a criterion to measure the overall domain specificity of a knowledge organisation system, based on domain-experts analysis. The authors also provide a first insight about using automated measures to determine the degree to which a given term can be considered domain specific. The resulting data set from the domain-experts’ evaluation can be reused as a gold standard for further research about these automatic measures.