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Seeks to examine the interaction effect of leadership and follower characteristics on follower self‐leadership, using hierarchical linear modeling.

Longitudinal data were collected using a questionnaire at two points in time, with ten weeks between each collection. These data facilitate the causal inference between leadership and follower need for autonomy (wave 1) and follower self‐leadership behaviors (wave 2). Hierarchical linear modeling (HLM) was used to analyze the hierarchical structure data.

Both empowering and directive leadership (group level) interacted with follower's need for autonomy (individual level) to enhance subsequent follower self‐leadership (individual level). That is, empowering leadership had a stronger positive effect on followers who were high on the need for autonomy, and directive leadership had a stronger negative effect on followers who were high on the need for autonomy. In summary, the influence of leadership on follower self‐leadership was contingent on follower need for autonomy. Overall, the results supported the view that attributes of the follower can be an important element in contingency theories of leadership.

This study does not include other possible individual characteristics, group level characteristics, and organizational level or environmental characteristics. A future research design might include organizational‐level characteristics.

Both the leadership context and the trait of the individual employee work hand in hand to produce true self‐leadership. Therefore, organizations need to develop empowering leaders who will, in turn, develop followers who are effective at self‐leadership.

This research contributes to the literature by testing a contingency model of leadership and follower self‐leadership. This study also demonstrated the usefulness of HLM to test interaction effects between group‐level variables and an individual‐level variable on individual‐level dependent variables.

There is a growing body of comparative research examining country differences in job satisfaction and its determinants. However, existing research cannot explain similarities in job satisfaction levels across very different countries, nor can it explain the differences between seemingly similar countries. Moreover, there has been no significant research conducted to date that has examined the country-level contextual conditions that are poised to impact worker satisfaction and its determinants. The paper aims to discuss these issues.

In this research, the author address this existing gap in the academic literature on job satisfaction by using non-panel longitudinal data from the International Social Survey Program (Work Orientations I, II, and III: 1989, 1997, and 2005) to examine cross-national differences in job satisfaction and its determinants. The author compare and combine previous international political economy theoretical work and hierarchical linear modeling (HLM) to examine global macro-level variables and their impact on worker satisfaction cross-nationally.

Study results demonstrate that both intrinsic and extrinsic work characteristics strongly impact worker job satisfaction. Furthermore, country by country regression and HLM results suggest that there are important country differences in both the perceived importance of various work characteristics and workers’ self-report experiences with both intrinsic and extrinsic work characteristics.

To get a clearer picture in the HLM analysis as to the full impact of these various country-contextual impacts on differences in perceived job characteristics and worker satisfaction, future research needs to examine a greater number and wider variety of countries, while exploring other theoretically relevant country-level variables that may help to explore country-level differences from these various cross-national theoretical frameworks. Additionally, a more diverse and greater number of participating countries would also potentially help in achieving levels of significance in the level-2 covariates in the HLM models.

Due to the fact the worker job satisfaction impacts firm performance and various measures of worker well-being, firms (regardless of economic sector or private/public status) need to be cognizant of these differences and unique challenges and work to tailor management philosophy and policy to create a unique work atmosphere that will benefit the interests of both the employer and the employee, as well as society at large.

While the nature of work has changed dramatically in the post-war era in response to economic shifts and an increasingly global economy, particularly over the past two decades, this paper examines the previously unexamined country-level contextual and global macro-historical variables driving differences in work quality and perceived worker satisfaction.

The objective of this study is to examine how the heterogeneity of the institutional environments within a single country influences International Financial Reporting Standards (IFRS) convergence and earnings quality based on a meso- and multi-level approach.

Using hierarchical linear modeling (HLM) to capture the between-group heteroskedasticity and within-cluster interdependence, this study investigates the simultaneous effect by incorporating institutional factors residing at different hierarchical levels and the interaction effects of factors within the same level on IFRS convergence and earnings quality in the largest IFRS adopter, China.

The results show that after IFRS convergence (i.e. 2007–2015), earnings quality decreases in terms of conservatism. However, the further analysis indicates that the strong institutional environment could mitigate the negative impact of IFRS on conservatism.

Consistent with the emphasis of heterogeneity within a country by Terracciano et al. (Science, 2005, 310 (5745)), this study indicates that the heterogeneity in the institutional environments and the simultaneous effect of the multilevel institutional environments within a single country cannot be ignored. This study also indicates that, equally important, research methodology plays a substantial role in investigating the outcomes of IFRS convergence. Finally, this study, based on an integrated theory, adopts a meso-paradigm linking macro- and micro-level institutions to provide comprehensive insights into IFRS convergence and conservatism.

Although the use of data from different levels is very common in international marketing research, the practice of employing multi‐level analysis techniques is relatively new. The paper aims to provide an application of a specific case of multi‐level modelling – where the dependent variable is dichotomous, which is often the case in marketing research (e.g. whether a consumer buys the brand or not, whether he/she is aware of the brand or not, etc.)

A hierarchical generalized linear model is employed.

Since this is a technical paper, the authors would like to emphasize the process rather than the empirical findings. In summary, the paper: provides a brief theoretical overview of Hierarchical Linear Modeling and Hierarchical Generalized Linear Modeling; illustrates the application of the method using the domains of consumers within countries and a dichotomous dependent variable; focuses on interpretation of log‐odds results; and concludes with practical issues and research implications.

The main value of this research is to demonstrate how to employ multi‐level models when the dependent variable is dichotomous. Multi‐level techniques are quite new in international marketing research, although nested data structures are relatively common in our field. This is a technical paper that guides the researchers as to how to apply and interpret the results when modeling such data with a dichotomous dependent variable.

This study aims at investigating the effect of an overall fit among strategy, environmental factors and organizational resources on firm performance, and the moderating role of industry on this relationship.

This paper uses hierarchical linear modeling to analyze the nested data structure from the financial and electronics companies in Taiwan’s stock market from 2011 to 2012.

The empirical results indicate that overall strategic fit is positively related to firm performance, and this relationship varies across financial industry and electronics industry.

This study provides important implications for both academic researchers and practitioners. From a theoretical aspect, this study integrates two research streams of strategic fit (external fit and internal fit) into an overall model of strategic fit, and has explored the moderating role of industry on the relationship between strategic fit and firm performance. In addition, this study has also used hierarchical linear modeling method to test the hypotheses, which has not been used in the previous strategic fit literature. From a practical aspect, the empirical results have derived implications for managers as to understand the effects of overall strategic fit on performance in different industry, which may be helpful for making decisions in specific industry context.

The paper aims to clarify the relationship between organizational identification, knowledge sharing and work characteristics. It proposes hierarchical linear modeling analysis of work context and social support climate with regard to organizational identification. The study aims to understand and prescribe the cross-level effects of a supportive climate and the effect of job design on organizational identification and knowledge sharing. Librarians need to share knowledge with their colleagues to provide timely responses for readers. Through a cross-level study, the authors' findings provide insights for both practice and academia.

Analysis approach in this paper consisted of the following steps. First, this study applied confirmatory factor analysis (CFA) to assess the validity and reliability of the authors' instrument. Second, this study checked the viability of aggregating the responses of the librarians to library-level constructs. Third, this study adapted hierarchical linear modeling (HLM) to examine the research hypotheses. HLM could be utilized to explain the nested data and simultaneously estimate the influence of factors from the different levels.

The paper provides empirical insights to support the relationship between task characteristics and organizational identification. Tasks with sufficient autonomy, variety, and feedback can improve the perception of organizational identification. Task characteristics and social support can reinforce knowledge sharing through shaping organizational identification.

As the sample libraries were all located in Taiwan, the research results may lack generalizability. Therefore, researchers are encouraged to further test the propositions in multiple cultures.

The paper includes implications for task characteristics and social support can reinforce knowledge sharing through shaping the organizational identification in libraries.

The results of cross-level analysis in this paper suggested that the variance of a supportive climate among libraries may exert an influence on knowledge sharing. This paper also confirmed organizational identification is also a partial meso-mediator for social support and knowledge sharing.

To identify the typical multilevel issues in social science, as well as illustrate the theoretical basis, hierarchical models and empirical exemplars of multilevel paradigm.

Hierarchical and multilevel data are extremely common in social systems, but multilevel analysis is constrained by statistical techniques. With the development of social system theory and empirical methods such as hierarchical structure modeling and latent growth modeling, multilevel paradigm can be used to analyze multilevel data. So it is necessary to identify typical multilevel phenomena in social science and discuss multilevel modeling techniques.

This paper identifies four typical multilevel phenomena in social system study: hierarchical and clustered sampling, collective construct research, longitudinal repeated measures, and event history analysis. Hierarchical structure modeling and latent growth modeling are effective multilevel analysis techniques in social science because of their advantages in the integration of social system research.

The quality and availability of multilevel data are the main limitations regarding which model will be applied.

The paper can aid the provision of effective multilevel models to social workers.

This paper provides information on application of multilevel modeling in social science.

The purpose of this paper is to identify the components of logistics value and examine their influence on customer satisfaction in e-commerce. This study investigates the moderation effect between those two variables using the overall service level in the different industries of e-commerce.

A total of 592 correctly filled questionnaires from telephone and web interviews (computer-assisted telephone interviews and computer-assisted web interviews) were scrutinized. Hierarchical linear modeling (as a part of a wider group of multilevel modeling studies) was used to verify the dependencies between variables from an organization and industry levels.

The logistics factors indicated and described in the paper differently affect the value for the customer. This value is subjective and dynamic. For this reason, the online seller should develop a system to create a sustainable value proposition. It is plausible due to the possibility of choosing the type of delivery, date of collection and change thereof, as well as that of returning the product. Because of all this, the customer decides on the way of the order execution and creates the value chain.

The developed model is aimed at identifying universal relationships that create the customer satisfaction mechanism for the logistics value. However, this may result in other aspects of customer satisfaction being neglected. The authors are aware that the creation of value by a company in e-commerce must be approached in a systematic manner.

The results obtained and the representativeness of the surveyed sample of companies lead to the formulation of implications for business practice. The conclusions of the research definitely indicate a need to build awareness of logistics value and its influence on customer satisfaction through the service level in the industry. Because of the identified components of the logistics value and industry characteristics, managers of online retailers can better run their businesses, increase customer satisfaction, and thus improve their performance.

It is the first study that concerns e-commerce in individual industries, with particular emphasis on logistics and its impact on customer satisfaction.

As organizations increasingly rely on teams to provide high levels of customer service, one's understanding and research methods related to teams must expand so that multiple hierarchical levels of an organization are analyzed effectively. This study aims to propose and test a model examining multi‐level team relationships.

Survey data from customer contact teams in a banking setting were analyzed using hierarchical linear modeling (HLM), a method appropriate for investigating individual and group level variables within an organization.

Results indicate that team‐member exchange, a group‐level variable, is positively associated with employee performance and organizational citizenship behavior (OCB), and explained variance in outcomes above and beyond that explained by the individual‐level relationship between the supervisor and subordinate.

Analyzing both individual‐ and group‐level variables through HLM explicates team processes and outcomes. While this study examines the banking environment, certainly, teams are an area fertile for additional study in a variety of industries.

The results provide support for the importance of team development and training as organizations increasingly use teams to provide critical customer service. Attention to the employee‐manager relationship and team member interactions will improve performance.

The paper extends understanding of important team member outcomes in an environment that increasingly relies upon teamwork to serve customers. It examines team‐member exchange and its effects on employee performance and OCB in the context of customer contact teams. Additionally, investigates leader‐member exchange in the context of team‐member exchange, a relationship that provides a more robust understanding of team processes.

The importance of regional strategy as a separate paradigm in the international business literature has grown in recent years, and the initial connections between regionalization and firm performance appear promising. What is lacking, however, is an empirical analysis quantifying the impact of regional effects on firm profitability. This topic is an important one for the field of international business, as drivers of firm profitability are some of the key motivators of research in international strategy. The aim of this paper is to empirically quantify the role of regional effects on the performance of service firms in a manner such that regional effects can be directly compared with country and firm effects on firm profitability.

Using a hierarchical linear model (HLM) with four levels, the proportion of variation driven by regional effects is estimated. These estimates are obtained from a data panel of 48,083 units from 7,129 service firms across the three triad regions (North America, Europe, and Asia Pacific) over a ten-year time-frame (1999-2008).

It was found that regional effects, in terms of relative importance, explain approximately 9 percent of the variance in firm performance. This pattern of results is consistent when the analysis was conducted during periods of increasing or decreasing profits, firm type, and ownership structure.

Within the context of international business, work on regional strategy/regionalization has emerged as a separate stream of literature. This study is one of the first to quantify the influence of regional effects on performance using a 4-level HLM model. Additionally, this paper demonstrates the application of a 4-level model, potentially increasing awareness of this technique and usage in other multilevel topics in the IB literature, which offers several avenues for future research.