Does justice affect brand advocacy? Online brand advocacy behaviors as a response to hotel customers’ justice perceptions

This study focuses on customers' information-sharing behavior in the context of online brand advocacy behavior regarding hotel brands. We aim to explain hotel customers' online brand advocacy behavior through three-sided justice evaluations (i.e., justice for employees, justice for the self, and global belief in a just world), and their hotel satisfaction. Hypotheses are tested by using survey data acquired from 688 individuals on Amazon's Mechanical Turk (MTurk) through partial least squares structural equation modeling (PLS-SEM). The findings show that customers' perceptions of justice for the self positively affect their hotel satisfaction, perceptions of justice for employees and the global belief in a just world positively affect online brand advocacy behavior, and hotel satisfaction also positively affects online brand advocacy behavior. We expand current research efforts on online brand advocacy research and provide theoretical and managerial implications for the development of marketing and management research and practice.     

辽宁省金融脆弱性研究

当前关于金融脆弱性的研究集中于国家这一宏观层面，对于省域金融脆弱性的研究还存在相当大的研究空间。正是基于这样一种相对创新性的视角，在对金融脆弱性现有研究进行综述的基础上对辽宁省的金融脆弱性的诱因进行了分析，并提出推动非银行金融机构的发展、拓展规模较大的银行的非利息收益以提升银行盈利能力以及全力清除不良贷款是应对辽宁省金融脆弱性的可行策略。     

Consumers’ luxury restaurant reservation session abandonment behavior during the COVID-19 pandemic: The influence of luxury restaurant attachment,emotional ambivalence,and luxury consumption goals

The purpose of this research is to examine how consumers’ attachment to luxury restaurants and their emotional ambivalence contribute to their reservation session abandonment during the coronavirus disease 2019 (COVID-19) pandemic. In addition, the moderating effect of luxury consumption goals (e.g., self-presentation motives, status consumption, and need for uniqueness) is examined. A total of 408 participants completed questionnaires, and the results reveal that luxury restaurant attachment significantly influences consumers’ emotional ambivalence, which in turn causes them to not complete their reservation sessions. Furthermore, the moderating effects of status consumption and need for uniqueness are supported.     

Contracting and Reporting Conservatism around a Change in Fiduciary Duties*

We exploit an influential 1991 Delaware court ruling to examine simultaneously two types of conservatism that play important roles in resolving creditor–owner agency conflicts: contracting conservatism and reporting conservatism. The ruling expanded managerial fiduciary duties in favor of creditors for Delaware-incorporated firms in the vicinity of insolvency. In those firms, following the ruling, debt contracts are less likely to include conservative adjustments to accounting numbers used for covenant compliance (i.e., contracting conservatism decreases), while public financial reporting becomes more conservative (i.e., reporting conservatism increases). The decrease in contracting conservatism is concentrated in firms that exhibit a greater increase in reporting conservatism, suggesting that reporting conservatism is more cost-effective in resolving agency conflicts. In addition, the substitution effect is more pronounced in firms facing greater business uncertainty and firms with greater board independence.     

Aid for trade and the quality of exports

This article studies how aid for trade (AfT) affects the quality of recipient countries’ exports. It shows that the quality effect is most discernible for AfT for assistance in trade policy: a 50% increase in the value of AfT received in this category is associated with a 0.5–1% increase in the quality of exports to the donor and other OECD countries. On average, the actual AfT received for assistance in trade policy leads to a 2% upgrade of the recipient country in the quality ladder of all developing countries. Around half of this quality effect is driven by the quality improvement of continued products in continued markets (intensive margin), and the other half by the quality upgrading of new products in continued markets and existing products in new markets (extensive margin).     

Drivers of eWOM engagement on social media for luxury consumers: Analysis,implications, and future research directions

The rapid industrialization and growth across the world have fostered the consumption of luxury fashion brands. Electronic word-of- mouth on social media (eWOM) is fast becoming an effective and germane strategy to engage luxury consumers through posting pictures, sharing reviews, and communicating information on platforms like Facebook, Instagram, and TikTok. Extant research has not examined the antecedents and drivers that lead to eWOM behavior. We leverage self-congruity theory and through its focal lens, our study addresses this research gap through a survey conducted with 453 consumers in Mexico, Latin America's fastest growing market. Our results indicate that need for status, susceptibility to normative influence, and luxury brand involvement, moderated by authentic pride and social media influencers lead to eWOM behavior on social media. We also demonstrate that luxury brand involvement and susceptibility to normative influence mediate the relationship between need for status and eWOM behavior on social media. The study provides important implications to managers and researchers by suggesting long-term actionable strategies for growth that can help luxury firms develop a sustainable competitive advantage over rivals and competitors.     

Is it U.S. GAAP or IFRS? Understanding how R&D costs affect ratio analysis

While financial reporting standards under U.S. GAAP and IFRS are fundamentally similar, differences do exist that may affect our analysis of company financial statements. This is particularly true when comparing a U.S. company following U.S. GAAP to a firm that uses IFRS. To illustrate, we compare research and development (R&D) accounting methods under both sets of standards and illustrate how they affect the analysis of financial results of firms in a specific industry—automotive manufacturers. Our results provide insight into settings in which differences in R&D accounting may have the greatest impact on financial analysis.     

Deep learning for modeling the collection rate for third-party buyers

This study evaluates a wide range of machine learning techniques such as deep learning, boosting, and support vector regression to predict the collection rate of more than 65,000 defaulted consumer credits from the telecommunications sector that were bought by a German third-party company. Weighted performance measures were defined based on the value of exposure at default for comparing collection rate models. The approach proposed in this paper is useful for a third-party company in managing the risk of a portfolio of defaulted credit that it purchases. The main finding is that one of the machine learning models we investigate, the deep learning model, performs significantly better out-of-sample than all other methods that can be used by an acquirer of defaulted credits based on weighted-performance measures. By using unweighted performance measures, deep learning and boosting perform similarly. Moreover, we find that using a training set with a larger proportion of the dataset does not improve prediction accuracy significantly when deep learning is used. The general conclusion is that deep learning is a potentially performance-enhancing tool for credit risk management.     

COMPARING PPP WITH TRADITIONAL PROCUREMENT: THE CASE OF SCHOOLS PROCUREMENT IN IRELAND

Advocates of public‐private partnerships (PPPs) argue that they can deliver public infrastructure more efficiently than traditional procurement through timelier completion and superior value for money. Despite these claims comparative analysis of the performance of both procurement methods has received scant attention in the PPP literature to date. This paper addresses this issue by providing an in‐depth, case‐based comparison of PPP versus traditional procurement in the schools sector in Ireland. Through detailed semi‐structured interviews with key stakeholders and an examination of the available documentation, we assess whether the key objectives of using PPP have been achieved. Overall, we find no evidence that PPP leads to faster delivery of infrastructure when the overall procurement process from contract notice to delivery is accounted for. In addition, we find only limited evidence to suggest that PPP results in better value for money.     

Effects of aid for trade on extensive and intensive margins of greenfield FDI

Using a panel dataset of 105 developing countries for the period 2003–15, this paper assesses the effects of Aid for Trade (AfT) on greenfield FDI flows to the aid‐recipient countries. Particularly, this paper classifies the total dollar value of greenfield FDI flows to each recipient country in terms of four different layers: the extensive and intensive margins of projects as well as the extensive and intensive margins of source countries. Applying the system GMM estimator, this paper finds that AfT not only increases the dollar value of FDI flows to the recipient countries but also helps diversify the greenfield projects and source countries. In addition, this paper finds that AfT has a greater effect for greenfield FDI from donor (developed) countries than from non‐donor (developing) countries. Among the three components of AfT, aid for trade‐related infrastructure and aid for trade policy regulations are found to have positive links with greenfield FDI, irrespective of source‐country groups, yet their effects are larger for developed source countries. In contrast, aid for building productive capacity hinders greenfield FDI flows from non‐donor countries, while it promotes greenfield FDI from donor countries. We offer some explanations for this finding.