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The present study aims to explore the concepts involved in the relationship between corporate social responsibility (CSR) and customer and employee satisfaction in service industries.

The research literature over the recent decade has been analyzed using a systematic review. Through thematic analysis and coding the findings of the final selected articles, the authors presented an integrative framework of the relationship between CSR and the satisfaction of critical stakeholders of service companies, namely, customers and employees.

The research framework encompasses six main categories called CSR, satisfaction, moderators, conditional variables, contextual variables and satisfaction outcomes. All categories but CSR are divided into customer and employee sections to make the research framework further comprehensible.

The results show that in service industries, employees need as much attention as customers, and CSR efforts to satisfy customers and employees can lead to several positive outputs for companies.

Failure of service companies to commit to their social responsibility may harm the environment, society’s ethics and laws and long-term corporate profitability. On the other hand, adherence to CSR can lead to social development and economic growth.

This study is one of the most comprehensive studies in the field of CSR and satisfaction, which simultaneously considers the two key stakeholders of a service company. In addition, it provides valuable avenues for further studies.

Joon Y. Park is one of the pioneers in developing nonlinear cointegrating regression. Since his initial work with Phillips (Park & Phillips, 2001) in the area, the past two decades have witnessed a surge of interest in modeling nonlinear nonstationarity in macroeconomic and financial time series, including parametric, nonparametric and semiparametric specifications of such models. These developments have provided a framework of econometric estimation and inference for a wide class of nonlinear, nonstationary relationships. In honor of Joon Y. Park, this chapter contributes to this area by exploring nonparametric estimation of functional-coefficient cointegrating regression models where the structural equation errors are serially dependent and the regressor is endogenous. The self-normalized local kernel and local linear estimators are shown to be asymptotic normal and to be pivotal upon an estimation of co-variances. Our new results improve those of Cai et al. (2009) and open up inference by conventional nonparametric method to a wide class of potentially nonlinear cointegrated relations.

The purpose of this research is to examine how pre-scandal associations and scandal types interactively influence consumer judgment and negative electronic word-of-mouth (eWOM).

Drawing from cognitive dissonance theory and associative memory network model, the online experiments (Amazon Mechanical Turk; Nexperiment 1 = 146 and Nexperiment 2 = 189) were conducted to examine the effects of positive pre-scandal associations (performance vs pro-social) and scandal types (performance-related vs -unrelated) on consumer blame and eWOM toward scandalized athletes. Data were analyzed by employing t-test (experiment 1), Multivariate Analysis of Covariance (MANCOVA) and PROCESS Model 8 (experiment 2) to test the hypotheses.

The findings highlight that positive pre-scandal association demonstrated both protecting and backfiring effects depending on the types of scandals. Specifically, when performance-related scandals emerged, consumers made more negative blame judgment of athletes with salient performance association, relative to pro-social association. Inversely, when performance-unrelated scandals occurred, athletes with salient pro-social association were more likely to be blamed. Regarding eWOM, consumers generate more negative eWOM when athletes with pre-performance associations are involved with performance-related scandals. This pattern of the result was not observed when athletes' pro-social association and performance-unrelated scandals were prominent.

The current work adds consumers' negative eWOM toward scandalized athletes to the literature as a predictor of how athletes' pre-scandal association with consumers and scandal types are related. The findings indicate that consumers feel greater dissonance and generate more negative eWOM when athletes' pre-scandal associations and scandal types are closely related.

This study aims to integrate reviewers’ and readers’ discrepant perspectives on extremely negative reviews. Specifically, this study examines the relationship between negative emotion intensity levels and reviews helpfulness on two platforms: integrated websites and social networking sites (SNS) to emphasize the role of platform types on customers’ purchase decisions.

This research adopts a mixed-method approach of business intelligence approach and quasi-experimental design. Study 1 performed text mining and Welch’s t-test to compare reviewers’ negative emotion intensity levels on two platforms. Study 2 adopted a 2*2 factorial quasi-experimental design to examine how intense negative emotions impact the perceived reviews helpfulness on two platforms. A 3*2 factorial design in Study 3 also tested social tie strength’s moderating effect between the intensity of negative emotions and review helpfulness.

The current study reveals that integrated website reviewers tend to express more extreme negative emotions than SNS reviewers. SNS and integrated website readers deem reviews that embed severe negative emotions as less helpful. The moderating role of social tie strength between extremely negative emotions on review helpfulness was insignificant in the study.

This study enriches the online review literature by comparing writers’ and readers’ perspectives on online reviews with extremely negative emotions across two online platform types: integrated websites and SNS. From the writers’ perspective, this study highlights anonymity and the presence of an audience as essential factors that reviewers consider in selecting an online review platform to express themselves. This research also sheds light on how readers’ perspectives on extremely negative reviews conflict with the presumptions of writers of extremely negative reviews on integrated websites by demonstrating that content embedding extremely negative emotions is less helpful regardless of platform type.

This research provides online negative review management strategies to platform and hotel managers. The findings suggest hotel and review platform managers should consider adopting review alignment or monitoring systems based on negative emotions intensity levels since readers on both platforms perceive reviews embedding extremely negative emotions as less helpful. Additionally, hotel managers can progress promotions to guests who share online reviews on SNS since SNS reviewers are more likely to attenuate their extremely negative emotions when writing reviews.

This research innovatively provides a comprehensive overview of negative reviews’ production and consumption process from reviewers’ and readers’ perspectives. This research also provides practitioners insight into the nature of two different platform types and the management of negative reviews on these platforms.

Competition among seaports is rapidly increasing due to various factors such as the global recession, resurgence of COVID-19, tight environmental regulations of IMO, sharp rise in ocean freight charges, increasing global uncertainties and growth in ship sizes. It is essential to have precise knowledge of shipping companies' port selection factors to secure the competitive advantage of seaports. This study aims to empirically analyze recent changes in the importance of port selection factors.

By employing a longitudinal study, this study conducted the t-test analysis. The first survey was conducted from January 2005 to April 2005. Then, the second survey was conducted in May 2021.

First, the importance of port facilities (berth length and the number of berths, shed and terminal areas, possession of adequate equipment and maximum berth size) increased significantly. Second, while ship and cargo safety were the critical port service factors in previous studies, speed, flexibility and reliability for handling cargo and berthing schedule were found to be crucial in this study. Third, the importance of ship arrival/departure frequency, route diversity and ship arrival/departure information systems increased when shipping companies selected the port.

This study has academic significance in that it reveals the changing importance of port selection factors in the 2020s and has taken the form of a longitudinal study on the importance of port selection factors from 2005 to 2021, moving beyond the cross-sectional approach. This study can provide valuable insights into and implications for port policymakers and managers when developing and formulating port policies and strategies.

Transient climate sensitivity relates total climate forcings from anthropogenic and other sources to surface temperature. Global transient climate sensitivity is well studied, as are the related concepts of equilibrium climate sensitivity (ECS) and transient climate response (TCR), but spatially disaggregated local climate sensitivity (LCS) is less so. An energy balance model (EBM) and an easily implemented semiparametric statistical approach are proposed to estimate LCS using the historical record and to assess its contribution to global transient climate sensitivity. Results suggest that areas dominated by ocean tend to import energy, they are relatively more sensitive to forcings, but they warm more slowly than areas dominated by land. Economic implications are discussed.

Using the theory of planned behavior (TPB) as a theoretical framework, this study investigates individual level psychological determinants of individuals word-of-mouth (WOM) intentions as a way to support corporate social advocacy (CSA).

An online survey (N = 505) using a Qualtrics panel was conducted.

Individuals' attitudes towards WOM, subjective norms, and self-efficacy was positively associated with their positive WOM intention, whereas perceived controllability over WOM behaviors was not associated with WOM intention. Age was negatively associated with WOM intention.

This study is one of the early attempts to test individual level factors in shaping individuals' WOM intention in response to CSA. This study also employed recent TPB argument and tested the role of self-efficacy and perceived controllability on behavioral intentions in the context of corporate communication. The findings of this study offer theoretical and practical insights to corporations when developing CSA campaigns and designing CSA messages.

The discrete Fourier transform (dft) of a fractional process is studied. An exact representation of the dft is given in terms of the component data, leading to the frequency domain form of the model for a fractional process. This representation is particularly useful in analyzing the asymptotic behavior of the dft and periodogram in the nonstationary case when the memory parameter d≥12. Various asymptotic approximations are established including some new hypergeometric function representations that are of independent interest. It is shown that smoothed periodogram spectral estimates remain consistent for frequencies away from the origin in the nonstationary case provided the memory parameter d < 1. When d = 1, the spectral estimates are inconsistent and converge weakly to random variates. Applications of the theory to log periodogram regression and local Whittle estimation of the memory parameter are discussed and some modified versions of these procedures are suggested for nonstationary cases.

This chapter proposes a test for a parametric specification of the autoregressive function of a given stationary autoregressive time series. This test is based on the integrated square difference between the empirical distribution function estimate and a convolution-type distribution function estimate of the stationary distribution function obtained from the autoregressive residuals. Some asymptotic properties of the proposed convolution-type distribution function estimate are studied when the model’s innovation density is unknown. These properties are in turn used to derive the asymptotic null distribution of the proposed test statistic. We also discuss some finite sample properties of the test statistic based on the block bootstrap methodology. A simulation study shows that the proposed test competes favorably with some existing tests in terms of the empirical level and power.