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The purpose of this paper is to analyze numerically the blowup in finite time of the solutions to a one-dimensional, bidirectional, nonlinear wave model equation for the propagation of small-amplitude waves in shallow water, as a function of the relaxation time, linear and nonlinear drift, power of the nonlinear advection flux, viscosity coefficient, viscous attenuation, and amplitude, smoothness and width of three types of initial conditions.

An implicit, first-order accurate in time, finite difference method valid for semipositive relaxation times has been used to solve the equation in a truncated domain for three different initial conditions, a first-order time derivative initially equal to zero and several constant wave speeds.

The numerical experiments show a very rapid transient from the initial conditions to the formation of a leading propagating wave, whose duration depends strongly on the shape, amplitude and width of the initial data as well as on the coefficients of the bidirectional equation. The blowup times for the triangular conditions have been found to be larger than those for the Gaussian ones, and the latter are larger than those for rectangular conditions, thus indicating that the blowup time decreases as the smoothness of the initial conditions decreases. The blowup time has also been found to decrease as the relaxation time, degree of nonlinearity, linear drift coefficient and amplitude of the initial conditions are increased, and as the width of the initial condition is decreased, but it increases as the viscosity coefficient is increased. No blowup has been observed for relaxation times smaller than one-hundredth, viscosity coefficients larger than ten-thousandths, quadratic and cubic nonlinearities, and initial Gaussian, triangular and rectangular conditions of unity amplitude.

The blowup of a one-dimensional, bidirectional equation that is a model for the propagation of waves in shallow water, longitudinal displacement in homogeneous viscoelastic bars, nerve conduction, nonlinear acoustics and heat transfer in very small devices and/or at very high transfer rates has been determined numerically as a function of the linear and nonlinear drift coefficients, power of the nonlinear drift, viscosity coefficient, viscous attenuation, and amplitude, smoothness and width of the initial conditions for nonzero relaxation times.

The purpose of this paper is to figure out in which way a hinterland-based inland depot model can help a shipping company in solving the empty container problem at a regional level. The repositioning of empty containers is a very expensive operation that does not generate profits. Consequently, it is very important to provide an efficient empty container management.

In this paper, the empty container problem is discussed at a regional repositioning level. For solving this problem, a mixed-integer linear optimization model is developed and validated by using the German hinterland as a case.

The findings show that the hinterland-based solution is able to reduce the total system costs by 40 per cent. In addition, total of truck kilometres could be reduced by more than 30 per cent too.

This research is based on German data only.

This paper closes the gap in empty container repositioning research by looking at the hinterland dimension from a single shipping company point of view.

This paper aims to explore the role of configurations of relationship quality dimensions for explaining sources of behavioral outcomes in the globalized manufacturing industry.

A joint analysis of behavioral and objective performance data from globalized manufacturing links perceptual customer metrics that relate to dimensions of relationship quality (i.e. attitudinal loyalty, perceived customer orientation, customers’ perceived innovativeness of the supplier and perceived customer influence on supplier innovation) with behavioral outcomes (i.e. share of wallet (SOW) and customer account profitability). Using data from a global business-to-business (B2B) customer survey together with archival performance data from a multinational mechanical engineering firm, a fuzzy set qualitative comparative analysis (fsQCA) is performed.

The fsQCA results suggest that perceptual customer metrics related to innovation can be relevant aspects of relationship quality, in line with Anderson and Mittal’s (2000) satisfaction-repurchase-profitability chain framework and its adaptation to SOW. However, the underlying complexities in the different combinations of attributes in the recipe are such that they are not equifinal in leading to higher SOW or higher profitability. This paper finds indications for non-linearities between perceptual measures investigated and profitability of customer accounts, with particular relevance for the role of perceived customer orientation, perceived product innovativeness of the supplier and attitudinal loyalty.

The analysis faces a number of limitations, starting with its reliance on cross-sectional survey data, which does not enable us to account for feedback mechanisms, for example, arising from customer perceptions regarding innovation aspects. The lack of a multidimensional conceptionalization of the perceptual customer constructs may have limited the analysis, considering also recent evidence from retail companies in the furniture sector in Spain, suggesting that the multidimensional conceptualization of relationship value explained satisfaction and loyalty levels to a greater extent than the one-dimensional conceptualization (Ruiz-Martínez et al., 2019).

In terms of managerial implication, the results suggest that customers perceive limited value in participating in the focal firm’s innovation value chain funnel, hence customer loyalty cannot be bought using simple incentive strategies. The results with regard to customer account profitability suggest that B2B customers investigated here may distinguish when interacting with their globalized supplier in the innovation funnel: they may see a positive customer value when the innovation is a product, and thus, relation-specific, whereas they may see limited customer value when innovation is considered in more generic terms (customers’ perceived influence on supplier innovation in general).

This paper starts from the premise that perceptual customer metrics can matter for supplier performance, as the customer relationship and customer value management research has shown. However, there is limited empirical evidence from globalized manufacturing sectors incorporating perceptual constructs in behavioral outcomes, and limited evidence assessing customer-perceived value in such sectors through alternate approaches to main-effects focused analyzes. We employ qualitative comparative analysis using fuzzy sets (Russo et al., 2019) to address these gaps, focusing on two key behavioral outcomes, namely, customer account profitability and SOW.

Over the past decades, many health authorities and public policy experts have traditionally relied on indicators that are dependent on a nation's economy, its health-care infrastructure advancements, and superiority in biomedical sciences and technology to predict potential infection rates should a health pandemic occur. One such commonly relied-upon indicator was that of the Global Health Security (GHS) Index. However, the coronavirus disease 2019 (COVID-19) pandemic has shown how such variables prove to be inaccurate in predicting the infection rates during a global health pandemic. Hence, this paper proposes the utilization of socio-cultural behavioral traits to predict a country's COVID-19 infection rates.

This is achieved by proposing a model involving the classification and regression tree (CART) algorithm and a Poisson regression against the six selected cultural behavioral predictors consisting of individualism, power distance, masculinity, uncertainty avoidance, long-term orientation, and indulgence.

The results show that all the selected cultural behavioral predictors are significant in impacting COVID-19 infection rates. Furthermore, the model outperforms the conventional GHS Index model based on a means squared error comparison.

The authors hope that this study would continue promoting the use of cultures and behaviors in modeling the spread of health diseases.

The authors hope that their works could prove beneficial to public office holders, as well as health experts working in health facilities, in better predicting potential outcomes during a health pandemic, thus allowing them to plan and allocate resources efficiently.

The results are a testament to the fact that sociocultural behavioral traits are more reliant predictors in modeling cross-national infection rates of global health pandemics, like that of COVID-19, as compared to economic-centric indicators.

The purpose of this paper is to study the drivers of service provider switching intention other than satisfaction and, additionally, analyse the moderating role of the type of service (utilitarian vs hedonic). Specifically, the authors study the effects of alternative attractiveness, post-purchase regret, anticipated regret and past switching behaviour.

A representative survey with 800 consumers of mobile phone services (utilitarian) and holiday destinations (hedonic) was carried out.

Satisfaction is not a significant antecedent of switching intention in the hedonic service and its effect is marginal in the utilitarian service. In the utilitarian service, the main predictor of switching intention is post-purchase regret, whereas in the hedonic service, the main determinants of switching intention are past switching behaviour and anticipated regret.

The main contribution of this study is the analysis of the determinants of provider switching behaviour that may explain abandonment by satisfied customers, to see if their influence is greater or smaller than that of satisfaction itself, which has been the most analysed variable. Furthermore, there are expected to be differences between utilitarian and hedonic services, an aspect which is also studied in this work.

The purpose of this paper is to measure the influence of corruption distance (CD) on foreign direct investment (FDI) with the characteristics of the value function from the Prospect Theory (PT) such as loss aversion and diminishing sensitivity.

Data are derived from Transparency International and the Organisation for Economic Co-operation and Development (OECD) and tested on the countries China, Germany, Italy, Japan, Korea, Russia, Spain and the UK and are analysed with a natural log (LN) regression model.

The findings indicate a negative asymmetric relationship for China, Germany, Korea, Spain and Russia. This means that negative performance on CD will not have greater impact on FDI outflows than positive performance on CD in the same country. Loss aversion, as well as diminishing sensitivity, as suggested by the PT, cannot be supported with the empirical results.

Its originality lies in contributing and extending knowledge on CD on FDI in several ways. First, it analyses the data of emerging and industrialized countries, namely, Russia, China, Germany, Italy, Japan, Korea, Spain and the UK. Second, a potential asymmetric impact is explained by the characteristics of the hypothetical value function of the PT. Third, it seeks empirical evidence by applying an econometric model developed to analyse the variables CD and FDI.

The purpose of this paper is to investigate the role of the retailer’s brand strength as a potential predictor of loyalty. It also examines the role of customer satisfaction (CS) to the retailer’s loyalty as well as its impact on the retailer’s brand strength.

The study was conducted in the grocery context and in a market under recession using the European Customer Satisfaction Index (ECSI) model. Data were collected through a telephone survey from 2,000 participants responsible for the household grocery shopping with a quota of 250 respondents from each of the leading grocery retailers in Greece. A formative measurement model was developed and the collected data were analyzed using partial least square path modeling.

The findings revealed that the strength of the retailer’s brand and CS influence retail loyalty and that brand strength mediate the strength of CS to loyalty. Results also suggested that the expectations and the perceptions toward the retailer’s product offering are the most important drivers of CS and loyalty. Thus, the study has proved the importance of the functional store attributes to CS and loyalty in the grocery store setting.

Research examining the suitability of the ECSI model in the grocery setting and in a market under economic crisis is scarce. This paper addresses these shortcomings by examining a customer loyalty model which incorporates the brand strength construct and investigates the role of brand strength as a potential predictor of loyalty as well as the role of CS in the brand strength and loyalty.

The contribution of the banking industry to the financial crisis of 2007/8 has raised public concerns about the financial soundness of banks around the world with many countries still suffering the backlogs of this crisis. The continuous emergence of such crises at both national and international levels increases governments', bank regulators' and financial market participants' need for reliable tools to assess the financial soundness of banks. In this context, this study investigates the financial soundness of the Kazakh banking sector, which is ranked by the World Bank as the first in the world in terms of the percentage of nonperforming loans (NPL) to total gross loans in 2012.

Using data about all Kazakh banks over the period January 01, 2008 to January 01, 2014, the study identifies a number of accounting indicators that influence the financial soundness of banks using principal component analysis (PCA). Then, it uses the outcomes of the PCA in a cluster analysis and groups the Kazakh banks into sound, risky and unsound banks at two points in time: January 01, 2008 and January 01, 2014. This methodology was further tested against a ranking system of banks and proved to be more reliable in detecting risky banks.

Fifteen financial ratios were initially selected as accounting indicators for the assessment of bank financial soundness. Using PCA, twelve indicators were isolated, which explain five principal components of capital adequacy, return on assets, profitability, asset quality, liquidity and leverage. Then using the “k-means” method, the results suggest a structure of the Kazakh banking sector on January 01, 2008 that includes two groups of banks: sound and risky banks. On January 01, 2014, this structure of the banking system has changed to include three groups of banks: sound, risky and unsound banks. Thus, in 2014 a new group of banks has emerged, i.e. financially unsound banks.

The proposed cluster-based methodology has proven to be a reliable tool to detect the financial soundness of Kazakh banks, which makes us advocate its employability for bank monitoring and supervision purposes.

This study is the first to employ a cluster-based methodology to assess the financial soundness of a banking sector. This methodology can be used at a micro-level to determine the structure of a banking sector. Also, it can be used to monitor any changes in the structure of a banking sector and provide early warning signals about the financial health of banks.

This study aims to test the compensatory consumption theory with the explicit hypothesis that China's new-rich tend to waste relatively more food.

In this study, the authors use Heckman two-step probit model to empirically investigate the new-rich consumption behavior related to food waste.

The results show that new-rich is associated with restaurant leftovers and less likely to take them home, which supports the compensatory consumption hypothesis.

Understanding the empirical evidence supporting compensatory consumption theory may improve forecasts, which feed into early warning systems for food insecurity. And it also avoids unreasonable food policies.

This research is a first attempt to place food waste in a compensatory-consumption perspective, which sheds light on a new theory for explaining increasing food waste in developing countries.