Chinese relationship management: a qualitative study of banking in New Zealand

This study investigates the relational factors and motivations of Chinese migrant consumers towards financial service providers in New Zealand. Using convergent interviews, a deeper understanding is developed of immigrants’ relational behaviour with service providers. These relationships with service providers are significantly influenced by traditional Chinese values and guanxi and relational embeddedness plays an important role in how they are developed. The research contributes a better understanding of the interplay between Eastern and Western cultures in service relationships among immigrant groups. A general theory of the Chinese perspective of customer relationship management is developed. The implications for how marketing practitioners manage their relationships with migrant customers are explored.     

Best classification algorithms in peer-to-peer lending

A proper credit scoring technique is vital to the long-term success of all kinds of financial institutions, including peer-to-peer (P2P) lending platforms. The main contribution of our paper is the robust ranking of 10 different classification techniques based on a real-world P2P lending data set. Our data set comes from the Lending Club covering the 2009–2013 period, which contains 212,252 records and 23 different variables. Unlike other researchers, we use a data sample which contains the final loan resolution for all loans. We built our research using a 5-fold cross-validation method and 6 different classification performance measurements. Our results show that logistic regression, artificial neural networks, and linear discriminant analysis are the three best algorithms based on the Lending Club data. Conversely, we identify k-nearest neighbors and classification and regression tree as the two worst classification methods.     

The signaling effects of education in the online lending market: Evidence from China

In this study, we use data from an online lending platform named Xinxindai in China to empirically study the signaling effects of education for the default risk of borrowers. Three dependent variables are created, namely, the probability of default, overdue payments and overdue amount, and probit models, count models and Tobit models are employed correspondingly. The number of universities in the “211 Project” of China at the city level is employed as the instrumental variable. The empirical evidence shows that education generally plays a strong signaling role in the identification of borrowers’ default risk in China. The negative marginal effect of education declines as borrowing times increase and as the marketization of regions deepens. This study helps to fill an important gap in the existing literature. Platforms and lenders can use educational level for reference in identifying the default risk of borrowers.     

Will FinTech make regional banks superfluous for small firm finance? Observations from soft information-based lending in Germany

Regional banks have a competitive advantage in that short distances to clients enable the use of soft information for superior lending decisions. If the ambition of FinTech start-ups to create superior screening and monitoring technologies materialises, this advantage would be diminished and regional banks would become superfluous for small firm finance. To explore this claim, the paper in hand analyses qualitative empirical data about the lending processes and rating system use of regional German savings banks. In essence, the results from participant observation and interviews clarify the importance of “real” soft information for critical lending decisions. The context specificity and limited verifiability of “real” soft information hamper it from being hardened through the use of rating systems and other bank-ICT. Though FinTech's scoring technologies may overcome the first limitation, it appears likely that in the course of scoring development “real” soft information will be systematically crowded out due to the manipulation problem. The paper expects improved access to finance for SMEs if FinTech solutions overcome both limitations of “real” soft information use, or if peer-to-peer lending and regional banks coexist. Deteriorated access to finance is expected if FinTech companies displace the relationship banking of regional banks due to enhanced competition, without preserving the advantages of “real” soft information with superior screening and monitoring technologies. The paper concludes with recommendations on how to prevent deteriorated access to finance for small firms by promoting fair competition and FinTech innovations.     

Market response to syndicated loan announcements from high-profile failed and acquiring banks during the global financial crisis

Previous studies that have examined the impact of the 2008 financial crisis on syndicated loans have ignored potential differences between lending banks by explicitly or implicitly aggregating all lenders together and focusing on borrower characteristics. One must jointly consider both borrower and lender to fully understand the complex role of the syndicate during this period. We consider the identity of the lender, with a focus on five major US banks that failed and their five corresponding acquirers. Our results highlight the distinct roles of investment and commercial banks and facilitate an understanding of relationship and transactional-based lending.     

The influencing factors of satisfaction and lending intention in online lending investment: an empirical study based on the Chinese market

This paper develops a platform‐based influencing factors model which considers value perception, risk prevention measure, non‐default experience, trust and incentive gap, to better examine the impact of platforms on investors’ satisfaction and lending intention based on the Chinese market. The results reveal that the first four factors positively influence the satisfaction of the investors, while the incentive gap has a negative impact, and there is a positive association between investors’ satisfaction and lending intention. Some specific features of China’s online lending market are identified, which provides valuable insights for online lending platforms and the government.     

The effect of activity identity fusion on negative consumer behavior

Negative consumer behavior is an important research topic as it explores consumer behaviors that threaten a brand's image and financial stability. However, prior research offers conflicting findings on whether a strong consumer‐brand relationship hurts or protects a brand after a market disruption or a brand transgression. To provide clarity on this issue, this work argues that disrupting the consumer‐activity relationship motivates consumers to reaffirm and protect their identity, thereby leading to negative consumer behavior. The data reveal that, after a brand‐initiated market disruption, consumers with high activity identity fusion are more likely to spread negative word‐of‐mouth, boycott the brand, and avoid repurchasing the brand in the future. Moreover, the data suggest that high brand identity fusion protects the brand during market disruptions; therefore, prior conflicting results may be due to the fact that the consumer‐activity relationship was not accounted for. Theoretically, this work establishes that consumers' relationship with their consumption activities has significant impacts on consumer behavior. Brand managers and marketers are urged to develop strategies that focus on strengthening the consumer‐brand relationship and not the consumer‐activity relationship.     

Interorganisational project dynamics: A longitudinal study of perceptual distance and client-contractor collaborative relationships

Despite the importance of good collaborative relationships in interorganisational projects, clients and contractors often develop adversarial relationships due to perceptual distance about key project issues. In this case study research, we investigated how perceptual distance emerges and changes over time, and how the collaborative relationship between client and contractor develops alongside these dynamics. In this exploration, we built upon agency theory and stewardship theory as complementary perspectives for understanding client-contractor collaborative relationships. We gathered quantitative and qualitative data in two projects, conducting three assessments in about one year. We found that perceptual distance increased and decreased over time, and that a reduction was typically associated with the collaborative relationship being characterized by stewardship rather than agency. These findings suggest that a regular assessment and evaluation of partners’ perceptions of critical project issues is warranted to timely detect and counteract perceptual distance. Moreover, partners would best adopt a stewardship orientation to reduce perceptual distance, although this may take considerable effort given the distributive nature of many pre-project negotiations.     

Alternative balanced scorecards built from paradigm models in strategic HRM and employment/industrial relations and used to measure the state of employment relations and HR system performance across U.S. workplaces

This paper constructs alternative balanced scorecards based on high‐performance work system (HPWS) and employment relations system (ERS) models. The models are depicted and compared in diagrams and used as framework skeletons for building separate HPWS and ERS scorecards, intended to provide a detailed data picture of the operational health and performance of an organization's employment/HR system and its operations, processes, and inputs/outputs. The scorecards are filled in with nationally representative data from 2,000+ U.S. workplaces using more than 50 employment/HR indicators, as reported by separate panels of managers and employees. The indicators for each workplace are aggregated into an overall HR/employment system score, ranked from low‐to‐high, and graphed as frequency distributions. These distributions provide a unique snapshot picture of the mean and dispersion of the state of employment relations and HR system performance for companies across the United State. They also reveal that “models matter” since the HPWS and ERS scorecards provide distinctly different evaluation assessments.     

The impact of COVID-19 on the G7 stock markets: A time-frequency analysis

We examine the co-movement of the G7 stock returns with the numbers of confirmed COVID-19 cases and causalities based on daily data from December 31, 2019 to November 13, 2020. We employ the wavelet coherence approach to measure the impact of the numbers of confirmed cases and deaths on the G7 stock markets. Our findings reveal that both the number of confirmed COVID-19 cases and the number of deaths exhibit strong coherence with the G7 equity markets, although we find heterogeneous results for the Canadian and Japanese equity markets, in which the numbers of COVID-19 cases and the deaths exhibit only a weak relationship. This evidence is more pronounced in the long-term horizon rather than the short-term horizon. Moreover, the lead-lag relationship entails a mix of lead-lag relations across different countries. We present the implications of these findings for both policymakers and the international investment community.