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.     

Facebook fan page: the effect of perceived socialness in consumer–brand communication

Facebook has become an important platform for a brand–consumer relationship channel. The current study investigates the influence of perceived socialness and its effect on consumers’ attitude toward brands. Participants (N = 404) were recruited in a large southeast university. A 2 (socialness: high vs. low)?×?2 (feedback control: high vs. low)?×?2 (brand image: high vs. low) between-subject design was conducted. The results of this study identified three important findings. First, high (vs. low) socialness elicited higher perceived relationship commitment, brand trust, and more favorable brand attitude. Second, the effect of socialness on brand attitude was moderated by brand image (positive vs. negative). Third, the mediation analysis showed that the effect of socialness (high vs. low) on brand attitude was fully mediated by perceived relationship commitment and brand trust.     

清徐县优势农业与旅游业协调发展研究

[目的]发展优势农业是改造传统农业,加快农业现代化的有效途径之一,旅游业作为国民经济新的增长点,两者协调发展更有利于增加农民收入,促进新农村建设,同时也是农村社会经济可持续发展的必然要求。[方法]文章通过文献查阅法了解清徐县优势农业葡萄及葡萄文化旅游业等方面的相关研究及研究成果,结合实证分析法通过协调发展度函数构建模型对清徐优势农业协调旅游业发展进行定量分析。[结果]清徐县优势农业和旅游业的综合评价指数从2004年的0.118 6上升到2016年的0.985 8,总体呈上升趋势,同时协调度13年间,2004~2008年介于0.221 5~0.490 5之间,处于失调发展阶段,2009年为过渡阶段,协调度为0.524 3,2010~2015年协调度介于0.626 7~0.685 8之间,处于初级协调发展水平,2016年协调度为0.701 7,发展到中级协调发展水平。优势农业与旅游业协调发展有利于区域经济水平的提高和农业收入的增加。[结论]推动优势农业与旅游业协调发展,清徐县需加大散户经营管理力度,切实有效地解决散户存在的实际问题,夯实优势农业的基础,为旅游业发展提供更大的发展空间。     

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.     

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.     

农产品电商与物流共生关系演化及协同度评价研究

农产品电商与物流协同将直接影响农产品的流通水平。运用共生理论,剖析了农产品电商与物流的共生关系机理与演化形式。利用微分方程分析了共生关系的演化过程,求解了共生关系的稳定条件。结果表明,协同共生均衡状态下产出水平得到提高,协同共生关系进入理想的稳定状态需要外部引导干预。对2013—2018年中国农产品电商与物流协同度变化的测量结果表明,当前中国农产品电商与物流协同尚处于初级阶段,共生关系表现为非互惠协同共生。     

A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures

This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Brownian distance correlation calculates the distance correlation between random vectors X and Y controlling for a random vector Z. Our test can detect nonlinear lagged relationships between time series, and when integrated with machine learning methods it can improve the forecasting power. We apply our method as a feature selection procedure and combine it with the support vector machine and random forests algorithms to study the forecast of the main energy financial time series (oil, coal, and natural gas futures). It shows substantial improvement in forecasting the fuel energy time series in comparison to the classical Granger causality method in time series.