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Seasonal fluctuation interference often affects the relational analysis of economic time series. The main purpose of this paper is to propose a new grey relational model for relational analysis of seasonal time series and apply it to identify and eliminate the influence of seasonal fluctuation of retail sales of consumer goods in China.

First, the whole quarterly time series is divided into four groups by data grouping method. Each group only contains the time series data in the same quarter. Then, the new series of four-quarters are used to establish the grey correlation model and calculate its correlation coefficient. Finally, the correlation degree of factors in each group of data was calculated and sorted to determine its importance.

The data grouping method can effectively reflect the correlation between time series in different quarters and eliminate the influence of seasonal fluctuation.

In this paper, the main factors influencing the quarterly fluctuations of retail sales of consumer goods in China are explored by using the grouped grey correlation model. The results show that the main factors are different from quarter to quarter: in the first quarter, the main factors are money supply, tax and per capita disposable income of rural residents. In the second quarter are money supply, fiscal expenditure and tax. In the third quarter are money supply, fiscal expenditure and per capita disposable income of rural residents. In the fourth quarter are money supply, fiscal expenditure and tax.

This paper successfully realizes the application of grey relational model in quarterly time series and extends the applicable scope of grey relational model.

Forecasts from dynamic factor models potentially benefit from refining the data set by eliminating uninformative series. This paper proposes to use prediction weights as provided by the factor model itself for this purpose. Monte Carlo simulations and an empirical application to short-term forecasts of euro area, German, and French GDP growth from unbalanced monthly data suggest that both prediction weights and least angle regressions result in improved nowcasts. Overall, prediction weights provide yet more robust results.

Inflation expectations are an important part of the transmission mechanism of the inflation targeting regime. As such, central bankers must study the inflation expectations of economic agents to anchor them close to the level of the inflation target. However, economic agents are affected by the past and current macroeconomic situation when they form their expectations concerning future inflation. Using survey data on inflation expectations in Czechia, we investigate the macroeconomic determinants of Czech analysts' and managers' inflation expectations. We find that both actual and past inflation have a substantial impact on inflation expectations of the agents surveyed. We also identify backward-looking behaviour among these agents: persistence in inflation expectations of up to two quarters was detected. Moreover, financial analysts formed inflation expectations more in line with economic theory, while company managers evinced expectations similar to those of consumers.

The purpose of this paper is to investigate the impact of a consumer confidence shock on GDP and different types of consumer spending during a slack state as well as a non-slack state of an economy.

The authors use the US quarterly data from 1960Q1 to 2014Q4 and apply Jorda’s (2005) local projection method to compute the impulse responses of macroeconomic variables to a consumer confidence shock. The local projection method allows us to include non-linearities in the response function.

In general, the response of output, following a consumer confidence shock, is similar in slack and non-slack states and indicate that an unfavorable confidence shock is contractionary. However, the intensity and duration of impact of a confidence shock on different components of spending are state dependent. Overall, a negative confidence shock appears to have a stronger impact on non-slack time than on a slack time.

Policy makers should be careful about undertaking a policy action that may affect consumer confidence adversely, particularly during an economic good time. An adverse confidence shock can trigger a downfall in a well-functioning economy and the dampening effect may last for several quarters before the economy rebounds.

US economy is subject to fluctuations; however, the literature on the impact of confidence shock in different economic states is limited. The incremental contribution of this paper is that it investigates how the consumers respond to the confidence shock in a state-dependent model. Furthermore, the authors use a more robust and alternative estimation method that tackles any non-linear problems.

Although the effects of both news sentiment and expectations on price in financial markets have now been extensively demonstrated, the jointness that these predictors can have in their effects on price has not been well-defined. Investigating causal ordering in their effects on price can further our understanding of both direct and indirect effects in their relationship to market price.

We use autoregressive distributed lag (ARDL) methodology to examine the relationship between agent expectations and news sentiment in predicting price in a financial market. The ARDL estimation is supplemented by Grainger causality testing.

In the ARDL models we implement, measures of expectations and news sentiment and their lags were confirmed to be significantly related to market price in separate estimates. Our results further indicate that in models of relationships between these predictors, news sentiment is a significant predictor of agent expectations, but agent expectations are not significant predictors of news sentiment. Granger-causality estimates confirmed the causal inferences from ARDL results.

Taken together, the results extend our understanding of the dynamics of expectations and sentiment as exogenous information sources that relate to price in financial markets. They suggest that the extensively cited predictor of news sentiment can have both a direct effect on market price and an indirect effect on price through agent expectations.

Even traditional financial management firms now commonly track behavioral measures of expectations and market sentiment. More complete understanding of the relationship between these predictors of market price can further their representation in predictive models.

This article extends the frequently reported bivariate relationship of expectations and sentiment to market price to examine jointness in the relationship between these variables in predicting price. Inference from ARDL estimates is supported by Grainger-causality estimates.

Since the transportation sector plays an important role in the initiation and propagation of business cycles, in previous chapters we developed output [transportation services output (TSI)] and other indicators to construct an index of coincident indicators for the U.S. transportation sector to identify its current state. We defined the reference cycle, including both business and growth cycles for this sector beginning in 1979 using both the conventional National Bureau of Economic Research (NBER) method and modern time series models. A one-to-one correspondence between cycles in the transportation sector and those in the aggregate economy was found; however, both business and growth cycles of transportation often start earlier and end later than those of the overall economy. Although the knowledge and inference based on coincident indicators can serve as an important reference for planning and other decision-making processes, these indicators are also subject to substantial lag due to data collection, processing and revision, underscoring the need to develop a system of leading indicators for the industry. Thus, in this chapter, we construct an index of leading indicators for the transportation sector as a forecasting tool using rigorous statistical procedures.

Introduction – In today’s intense competitive environment, businesses that want to have a sustainable competitive advantage must put the customer at the centre of all their activities and create customer loyalty by offering products and services that will provide customer satisfaction. One of the key elements of ensuring customer satisfaction is the effective handling of customer complaints, which is defined as the customers expressing their dissatisfaction with unmet expectations and unsatisfied needs verbally or in writing. The concept of a complaint as a response of customers’ dissatisfaction with the products and services they experience is an invaluable feedback mechanism for businesses to resolve issues relating to their products and services.

Aim – The aim of this chapter is to emphasise the importance of the concept of complaint as an important part of customer relations management and an effective marketing tool for the tourism sector. As a service sub-sector, the simultaneous production and consumption of services in the tourism sector ensures customer satisfaction more than concrete products, due to their inseparable nature. For this reason, handling, evaluating and finalising customer complaints has an important function and value in providing the necessary information for tourism enterprises to become aware of their deficiencies and mistakes. Complaint management has started to play an even more critical role for the tourism industry in preventing customer losses due to dissatisfaction, especially considering the shrinkage in demand in the sector due to the COVID-19 pandemic.

Method – Firstly the concept of complaint and the importance of complaints for businesses were explained, customer complaint behaviour and the factors affecting this behaviour were examined in detail, the concept of online complaint was mentioned and the subject was evaluated in terms of tourism businesses.

Results – While the effective management and resolution of complaints should be seen as a goal by every tourism business, it is vital that they understand customer complaint behaviours, the factors affecting this behaviour and how complaints should be managed in a way that will result in favour of the business.

Conclusion – A complaint management process that enables customers to easily report their complaints to businesses and produces solutions as soon as possible will positively affect customer satisfaction. In this context, in order to reduce the negative effects on tourism enterprises, especially through the pandemic, business need to have clear and easy-to-access procedures, provide a quick response, show reliability and consistency in providing a solution, keeping the complainant informed of progress, have employees who can communicate with empathy and courtesy, have enough employees to deal with the situation, and adopt proactive approaches to prevent complaints rather than reducing the volume of complaints.

Originality/Value – This research contributes to the literature in terms of complaining behaviour, examining the factors affecting this behaviour and emphasising the importance of the concept of complaints in the tourism sector. In addition, the research is important in terms of examining the contributions of an effective complaint management system in reducing the negative effects of the COVID-19 pandemic on the tourism sector, which is one of the sectors mostly affected on a global scale.

This study provides empirical evidence on the existence of a mood effect in Korea Stock Market. Given the assumptions that changes in the Consumer Expectation Index and the numbers of suicides proxy for the social mood, I find that the aggregate stock market moves with the changes of investor sentiment, on average. The relation between the KOSPI and mood variables representing for investor sentiment is economically and statistically significant. For example, a 10% increase of the CEI relative to the previous month leads to a 14.7% rise of the KOSPI. The magnitude of the mood effect is even larger on the small cap stocks, especially in the KOSDAQ market. The contemporaneous changes in the KOSPI affected by the changes of investor sentiment are mostly reversed in the next month, suggesting that the mood effect is short-lived and seems to be unrelated to the fundamental information.

The intangibility of services presents a number of problems for the measurement of quality and customer satisfaction. Proposes a simple index which can be applied to ordinal or cardinal data and will provide a convenient aggregate summary of the extent to which a product or service meets consumer expectations. The index, though simple, is robust, and is applied to the problem of analysing the quality of banking services provided to small firms in the United Kingdom.

Given the economic downturn, the purpose of this study was to determine if a relationship exists between economic perceptions and consumers' motivation to consume for status and if this relationship was moderated by education level.

A stratified random sample of adult consumers in the southeastern USA were surveyed by telephone. The hypotheses were tested utilizing structural equation modeling.

The results indicated that those consumers with a lower level of perceived economic welfare (i.e. see the economy and their family's financial situation as worse this year versus last year) were less motivated to consume for status. Furthermore, this relationship was positively moderated by education. No relationship was found between consumer confidence (i.e. consumers' perceptions of the economy in the future year) and status consumption. The results suggest that those consumers who perceive themselves to be financially better off this year versus last, particularly those more educated, are more motivated to consume for status.

The main research limitation was that the sample skewed to be older, female and Caucasian, though the sample did match Census figures for the critical variable of education. Additionally, the phone response rate was 9 percent, but it is important to recognize that this was for a non-student sample.

The results suggest that marketers, targeting luxury consumers in the current stagnant economy, aim for more educated consumers who see their economic welfare as improving. This implication stems from the research findings revealing that consumers who feel they are recovering economically from the recent economic downturn, especially those with higher education levels, may more likely be status consumers.

With the democratization of luxury there is renewed interest in luxury consumption research. While research suggests there is a relationship between economic conditions and status consumption, few studies have measured consumer economic perceptions in relation to status consumption and none have examined how education may play a moderating role in explaining why people buy luxuries in a tough economic climate.