Personalized managerial response and negative inconsistent review helpfulness: The mediating effect of perceived response helpfulness

Understanding the effect of managerial response on online review management has attracted the attention of scholars in recent years. However, the effect of personalized managerial response on the negative inconsistent review is a lack of evidence. This study investigates how personalized managerial responses influence negative review helpfulness according to the various levels of review inconsistency and the underlying mechanism behind the effect. We adopted a secondary data analysis based on the TripAdvisor dataset and used an online experiment study to investigate the impact mechanism. Findings reveal that the personalized managerial response positively influences review helpfulness, review inconsistency (negative rating with positive textual sentiment) moderates the effect of personalized managerial response on review helpfulness, and perceived response helpfulness mediates the above relationships. More specifically, personalized managerial response to negative inconsistent reviews has a pronounced effect on consumers’ perception of response helpfulness and their evaluation of review helpfulness. This study improves the current understanding of managerial responses, and provides practical guidance for hoteliers, consumers, and travel websites.     

Fifty years of The Financial Review: A bibliometric overview

The Financial Review (FR) is a highly regarded journal publishing original empirical, theoretical, and methodological research in all areas of financial economics. It celebrated its golden jubilee year in 2018. Using bibliometric techniques, we analyze the journal's impact, prominent topics, most prolific authors, and their affiliated institutions and countries. Our analysis also identifies the most often cited articles at different points in the journal's history. Using textual data analytics, we identify the most frequent themes discussed between 1969 and 2018 by decade.     

Why do auditors fail? What might work? What won’t?†

Auditing failures and scandals have become commonplace. In response, reformers (including the Kingman Review in the U.K. and a recent report of the U.K.’s Competition and Market Authority) have proposed a variety of remedies, including prophylactic bans on auditors providing consulting services to their clients in the belief that this will minimize the conflicts of interest that produce auditing failures. Although useful, such reforms are already in place to a considerable degree and may have reached the point of diminishing returns. Moreover, this strategy does not address the deeper problem that clients (or their managements) may not want aggressive auditing, but rather prefer a deferential and perfunctory audit. If so, auditors will realize that they are marketing a ‘commodity’ service and cannot successfully compete based on their quality of services. Rationally, they would respond to such a market by seeking to adopt a cost-minimization strategy, competing by reducing the cost of their services and not investing in new technology or higher-priced personnel.

What could change this pattern? Gatekeepers, including auditors, serve investors, but are hired by corporate management. To induce gatekeepers to better serve investors, one needs to reduce the ‘agency costs’ surrounding this relationship by making gatekeepers more accountable to investors. This might be accomplished through litigation (as happens to some degree in the U.S.), but the U.K. and Europe have rules that discourage collective litigation. Thus, a more feasible approach would be to give investors greater ability to select and remove the auditor. This paper proposes a two part strategy to this end: (1) public ‘grading’ of the auditor by the audit regulator in an easily comparable fashion (and with a mandatory grading curve), and (2) enabling a minority of the shareholders (hypothetically, 10%) to propose a replacement auditor for a shareholder vote. It further argues that both activist shareholders and diversified shareholders might support such a strategy and undertake it under different circumstances. Absent such a focus on agency costs, however, reformers are likely only re-arranging the deck chairs on the Titanic.     

Machine Learning and Expert Judgement: Analyzing Emerging Topics in Accounting and Finance Research in the Asia–Pacific

In this paper, we focus on the question to what extent machine learning (ML) tools can be used to support systematic literature reviews. We apply a ML approach for topic detection to analyze emerging topics in the literature—our context is accounting and finance research in the Asia–Pacific region. To evaluate the robustness of the approach, we compare findings from the automated ML approach with the results from a manual analysis of the literature. The automated approach uses a keyword algorithm detection mechanism whereby the manual analysis uses common techniques for qualitative data analysis, that is, triangulation between researchers (expert judgement). From our paper, we conclude that both methods have strengths and weaknesses. The automated analysis works well for large corpora of text and provides a very standardized and non-biased way of analyzing the literature. However, the human researcher is potentially better equipped to evaluate current issues and future trends in the literature. Overall, the best results might be achieved when a variety of tools are used together.     

Racism in tourism reviews

Racism is increasingly recognised as a key driver of unfair inequalities in power, resources and opportunities across racial groups. A comprehensive understanding of racism is beneficial to activist groups, policymakers and governments. Traditional approaches, such as surveys and interviews, are usually time-consuming and inefficient in capturing the occurrence of large-scale racism. In this study, we utilise routinely collected data available on tourism websites to assess self-reported racism in the tourism domain. We present a data acquisition procedure that collects racism-related reviews from the Internet at the global scale and then utilise statistics and natural language processing techniques to analyse and explore racism in terms of its tendency, distribution, semantics and characteristics. The effectiveness of the proposed method is demonstrated in a case study, in which we acquire racism-related data at the global scale and validate the impact of racial discrimination on tourists’ experience.     

Disentangling acquisition experience: A multilevel analysis and future research agenda

Research interest in firms repeatedly involved in acquisitions has increased over the past decade. However, this increase has remained unmatched by efforts to integrate what is known, leaving the acquisition experience research field scattered, in turn hampering further theoretical and empirical progress. Taking a broad approach to experience, we review 106 empirical studies published in leading journals that focus on the effects of past acquisitions on subsequent ones. We discover three distinct but complementary ways in which research has dealt with experience. Moreover, research on acquisition experience has drawn conclusions on three important but insufficiently integrated levels of analysis. Our review delineates and systematises the current theoretical and empirical progress in acquisition experience research and outlines a future research agenda.     

Unraveling the interplay of review depth,review breadth,and review language style on review usefulness and review adoption

To examine whether long reviews are uniformly more useful to readers, this study utilizes the experimental design approach to investigate the interplay of review depth, review breadth, and review language style on readers’ perceived usefulness and adoption intention of online hotel reviews. Drawing on the results from two experiments, review depth is proven to exert a positive impact on readers’ review usefulness and adoption intention. The moderating role of review breadth is verified, and the positive effect of review depth on review usefulness is attenuated (accentuated) when review breadth is high (low). The moderating role of review language style is also confirmed, and the result shows longer reviews written in literal language are considered more useful to readers than those written in figurative language. Being one of the first studies examining the interplay of review content and review style on review usefulness, this study provides important theoretical and practical contributions.     

基于科学的企业内部治理问题：文献综述与研究展望

迄今为止,基于科学的企业研究已经取得重大进展。尝试对基于科学的企业内部治理研究成果进行梳理,以基于科学的企业内涵、创业者角色、科学家团队治理、董事会治理、股东治理、高管治理为逻辑框架,对基于科学的企业内部治理研究现状进行总结归纳。在此基础上,从基于科学的企业治理机制视角提出未来研究方向,包括企业权力配置、激励机制设计、人员配置等系列研究问题。提出的未来研究方向可丰富和拓展基于科学的企业治理理论框架,为理解和指导中国情境下基于科学的企业治理实践带来启示。     

基于大数据环境的财务报销自动审核系统构建

为了有效地解决当前企业财务报销审核系统中审核差错大、运行效率低的问题,在大数据分析的基础上,对自动财务报销审核系统进行了优化。结合数值概率算法,对大量财务报销数据进行合理分类,并将分类后的数据传输到财务项目配置模块进行审批。优化财务审核安全评价流程,检查审核处理结构的准确性。对系统服务器和处理器模块的硬件配置进行了优化,达到了优化财务自动报销审核运行效果和准确性的设计目标。实验证明,基于大数据分析的财务报销自动审核系统的财务审核差错率较传统系统明显降低,系统运行效率较传统审核系统提高20%-50%。