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This paper aims to discuss multilevel modeling for longitudinal data, clarifying the circumstances in which they can be used.

The authors estimate three-level models with repeated measures, offering conditions for their correct interpretation.

From the concepts and techniques presented, the authors can propose models, in which it is possible to identify the fixed and random effects on the dependent variable, understand the variance decomposition of multilevel random effects, test alternative covariance structures to account for heteroskedasticity and calculate and interpret the intraclass correlations of each analysis level.

Understanding how nested data structures and data with repeated measures work enables researchers and managers to define several types of constructs from which multilevel models can be used.

The purpose of this paper is to develop a structural relationship model to study the relationship between causes and effects of poor communication and information exchange in construction projects using Smart-PLS.

The first method of this research is to identify the causes and effects factors of poor communication in construction projects from the extant of literature. The data used to develop the model was collected using a questionnaire survey, which targeted construction practitioners in the Malaysian construction industry. A five-point Likert type scale was used to rate the significance of the factors. The factors were classified under their relevant construct/group using exploratory factor analysis. A hypothetical model was developed and then transformed into Smart-PLS in which the hypothetical model suggested that each group of the cause factors has a direct impact on the effect groups. The hypothesis was tested using t-values and p-values. The model was assessed for its inner and outer components and achieved the threshold criterion. Further, the model was verified by engaging 14 construction experts to verify its applicability in the construction project setting.

The study developed a structural equation model to clarify the relationships between causes and effects of poor communication in construction projects. The model explained the degree of relationships among causes and effects of poor communication in construction projects.

The published academic and non-academic literature introduced many studies on the issue of communication including the definitions, importance, barriers to effective communication and means of poor communication. However, these studies ended up only on the general issue of communication lacking an in-depth investigation of the causes and effects of poor communication in the construction industry. The study implemented advanced structural modeling to study the causes and effects. The questionnaire, the data and concluding results fill the identified research gap of this study. The addressed issue is also of interest because communication is considered one of the main knowledge areas in construction management.

Industry 4.0 technologies are promising to increase manufacturing companies' performance through the new knowledge that such digital technologies allow to create and manage within the firm boundaries and through customer interactions. Despite the great attention on the Industry 4.0 adoption paths, little is known about the relationships with previous waves of digital technologies, namely, information and communication technologies (ICTs), and how different groups of both types of technologies link to knowledge and its related performances.

The study employed a quantitative research design using a survey method. Submitting the questionnaire to entrepreneurs, chief operation officers or managers in charge of the operational and technological processes of Italian manufacturing firms, 206 respondents stated that their firm has adopted at least one of the seven Industry 4.0 technologies investigated.

The findings of the study highlight the positive relationship between ICT and Industry 4.0 technologies in terms of both intensity and groups of technologies (Web-based, Management and Manufacturing ICT; Operation, Customization and Data-processing 4.0), and how technologies affect knowledge-related performances in terms of products and processes, job-learning, product-related services and customer involvement.

This study is one of the first attempts to link groups of ICT to groups of Industry 4.0 technologies and to explore the effects in terms of knowledge-related performances as a measure of technology use. The study shows strong path dependency among ICT, Industry 4.0 and knowledge performance, enriching the literature on technological innovation and knowledge management.

China is currently developing and promoting an industrial cluster policy at the government level. By enacting the ‘Opinion on promoting industrial cluster development’, China is supporting the development of industrial clusters. Building an industrial cluster is done by using a single factor but requires many additional factors like regional characteristics, competitiveness factors are also diversified. To evaluate the competitiveness of the Chinese automobile industry cluster, a competitiveness element index should be developed and a competitiveness evaluation method is needed to evaluate the importance of each element. To accomplish this objective, this research applied the analytic hierarchy process (AHP) and focused on the importance of the competitiveness elements.

This research investigated the character is tics regarding cases of clusters and also analyzed the competitiveness of the Changchun automobile cluster located in northeastern China. The purpose of this research is to help Korean enterprises who enter China in the hopes that Korea will emerge as a top automobile production country.

To cope with climate change and achieve the dual carbon goal, China has actively promoted the implementation of carbon trading pilot policy, among which the power industry plays an important role in China’s carbon emission reduction work. The purpose of this paper is to study the influence of carbon trading policy on the energy efficiency of power industry and achieve the comprehensive goal of carbon emission reduction, carbon peak and carbon neutralization.

This paper constructs the difference-in-differences model based on 2012–2019 provincial data to study the impact of carbon trading policy on energy efficiency in the power industry and its effect path. Heterogeneity analysis was conducted to compare the effects of carbon trading policy in eastern, central and western regions as well as at different levels of power structures.

Carbon trading policy can significantly improve the energy efficiency of the power industry, and the policy effect is more significant in eastern and western regions and areas with high power structure. Mechanism analysis shows that carbon trading policy mainly influences the energy efficiency of power industry by environmental protection investment, power consumption demand and industrial structure.

This paper uses provincial panel data to deeply study the influence of carbon trading policy on energy efficiency of the power industry and its effect path. By constructing the difference-in-differences model, this paper empirically analyzes the governance effect of carbon trading policy. Meanwhile, it controls individual and time effects to solve the endogeneity problem prevalent in previous literature.

The purpose of this paper is to examine the financial factors across multiple levels of analysis that influence the performance effects of the unrelated diversification strategy, including institutional-, industry- and firm-levels.

Using a unique panel dataset of Italian firms from 1980 to 2010, the paper tests hypotheses on how industry external financial dependence and the firm's financial constraints both separately and jointly alter the performance benefits of unrelated diversification in contexts with financial market inefficiencies.

Unrelated diversification increases performance in weak financial contexts and such positive effect is enhanced by greater industry external financial dependence and greater firm financial constraints. However, as financial markets develop, the moderating effects of firm financial constraints shrink.

The study highlights the importance of recognizing the multiple financial contingencies that may alter the benefits of the unrelated diversification strategy, suggesting caution in its pursuit to boost firm performance.

The authors develop a theoretical framework that explains the performance outcomes of unrelated diversification, linking the benefits of an internal capital market (ICM) with the financial context of the firm and offering a fine-grained analysis that moves beyond the advanced/emerging economy dichotomy. Furthermore, leveraging on the unprecedented time frame of the empirical analysis, the paper highlights the crucial role of industry- and firm-level financial contingencies and demonstrates that their effects change at varying levels of development of the financial context.

This paper aims to provide swift feedback to readers and investors on the early effect of novel coronavirus (COVID-19) pandemic outbreak on tourism industry.

Three leading consolidators of hotel accommodations, airline tickets and travel services in the tourism industry around the globe, namely, Booking Holdings Inc., Expedia Group and Trip.com Group Ltd. are chosen in this study. First, numerical description is performed on their shares prices and a set of control variables to compare their performances before and during the lockdown because of COVID-19 outbreak. Next, this paper estimates ordinary least squares models with and without exponential generalized autoregressive conditional heteroskedastic specification to establish the nature, significance and magnitude of the pandemic’s early effect on the shares performance of these online travel companies (OTCs).

This paper discovers a rapid decline in the performance of tourism industry amid the pandemic outbreak, from the perspective of three leading OTCs, which derive their profits from tourists by providing them online hotel reservation, air-ticketing and packaged-tour business services around the globe. These significant adverse direct and indirect effects testify that tourism-related businesses are extensively locked down by the pandemic outbreak.

Future studies are encouraged to examine each of the tourism sectors for individual effects.

This paper provides implications for investors to protect their wealth, and for policymakers to ensure sustainability of tourism industry in the pandemic outbreak and in the future.

From the perspective of corporate finance, this paper empirically quantifies the early effect of COVID-19 on tourism industry for a quick snapshot.

Longitudinal studies have shown that consumer satisfaction has increased over the last 15 years, whereas trust and loyalty have decreased during the same period. This finding contradicts the trust–value–loyalty model (TVLM), which posits that higher satisfaction increases consumers' trust, value and loyalty levels. To explain this counterintuitive trend, this study draws on models of trust formation to integrate the stereotype content model and the TVLM. It argues that consumers' occupational and industry stereotypes influence their trust, value and loyalty judgments through their trusting beliefs regarding frontline employees and management practices/policies.

The study was conducted among 476 consumers who were randomly assigned to one of five service industries (apparel retail, airlines, hotels, health insurance or telecommunications services) and asked to rate their current service provider from that industry.

The results suggest that both occupational and industry stereotypes influence consumers' trusting beliefs and trust judgments, although only the effects of industry stereotypes are transferred to consumers' loyalty judgments.

The results of the study indicate that industry stereotypes have become increasingly negative over the last decades, which has a dampening effect on the positive effects of satisfaction.

This study provides guidelines for practitioners regarding the management of frontline employees and the development of consumer trust, value and loyalty.

This is the first study to propose and test an explanation for the counterintuitive trend concerning customer satisfaction, trust and loyalty. It is also the first to examine the roles of multiple stereotypes in the relationship between consumers and service providers.

In recent years, many companies have decided to decertify from their previously adopted corporate social responsibility (CSR) standards. The aim of this paper is to explore the phenomenon by focusing on the most important auditable CSR standard: Social Accountability 8000 (SA8000).

First, an event study is performed on a dataset composed of 136 SA8000 decertified public listed companies to analyse the possible relationship between certification, decertification and firms’ operating performance. Second, the authors shed light on the differences between 94 SA8000 (still) certified and the abovementioned 136 decertified firms. Finally, 10 interviews are conducted with decertified firms in the dataset to deepen the outcomes of the previous analyses.

The results show that, despite an initial positive effect in terms of sales and profitability, decertified companies experienced a reduction in productivity and profitability in the years following the certification, while positive outcomes emerged after the decertification. The study also highlights that certified and decertified firms differ in terms of home country, industry and labour intensity.

The paper contributes to the literature by opening the debate on an important but unexplored research area: the decertification from the most popular CSR standard, i.e. SA8000, and its relationship with firms' performance. In doing this, it also highlights the main differences between decertified and certified companies.

The government of Korea considers the promotion of Free Trade Agreements (FTA) as necessary to develop its economy into an open trading nation. As for the countries with which the Korean government is actively investigating possible FTAs, there are Japan, Singapore, the Association of South East Asian Nations (ASEAN,) and Mexico. For the time-being, the FTA with Japan seems to be a critical one in practicing Korea s FTA policy. Recently, Korean industries show negative positions against a Korea-Japan FTA, with strong opposition from the labor union insisting that it is evident that Korea will sustain damages in the short-run and the dynamic (long-term) benefits are still ambiguous and uncertain. Regardless of whether their argument is correct or not, it will be difficult for Korea to conclude the FTA with Japan unless there is concrete confidence of balanced economic gains through the FTA between the two countries.