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The purpose of this paper is to identify the dimensions of service quality and examining the interrelationships among behavioral intentions, customer satisfaction, perceived value, corporate image and service quality in the gaming industry. A multi-level and hierarchical model is used as a framework to synthesize the effects of customer satisfaction, perceived value, corporate image and service quality on behavioral intentions of customers in the gaming industry.

The data used in this study were based on a sample of 470 at a newly built casino in Macau. Data were analyzed using exploratory factor analysis and regression analysis.

The findings support using a multi-level model consisting of three primary dimensions and ten sub-dimensions to conceptualize and measure perceived service quality. Perceived service quality significantly influences perceived value and corporate image, respectively. In addition, perceived value and corporate image are main determinants of customer satisfaction. Also, customer satisfaction and corporate image significantly affect behavioral intentions.

This is the first study synthesizing behavioral intentions, customer satisfaction, perceived value, corporate image and perceived service quality in a Macau casino setting.

This study aims to fill a conceptual gap by identifying the dimensions of green experiential quality and empirically examining the interrelationships among green experiential quality, green equity, green image, green experiential satisfaction and green switching intention. A multi-dimensional model is used as a framework to synthesize the effects of green experiential quality, green equity, green image and green satisfaction on green switching intention of green hotel customers.

The data used in this study were collected from a sample of 535 customers staying in one green hotel of Taipei City, Taiwan. Data were analyzed using structural equation modeling and hierarchical regression analysis.

The findings support a multi-dimensional model consisting of four dimensions (interaction quality, physical environment quality, access quality and administration quality) to conceptualize and measure perceived green experiential quality. Perceived green experiential quality significantly influences green equity and green image, which, in turn, result in green experiential satisfaction. Green switching intention is influenced by green experiential satisfaction and green image. However, outcome quality is not a component of perceived green experiential quality, which, in turn, insignificantly results in green experiential satisfaction. Green image plays a role in moderating the relationship between green experiential quality and interaction quality, outcome quality, access quality and administration quality.

To increase green experiential quality and green equity, enhance green image and green experiential satisfaction and decrease green switching intention, the finding of this study will help green hotel management to develop and implement market-oriented service strategies.

This is the first study to synthesize the effects of green experiential quality, green equity, green image and green experiential satisfaction on green switching intention in a green hotel setting.

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.

Previous literature has compared the effectiveness of different styles of leadership, yet most of this research has not compared different levels of analyses regarding leader styles or behaviors. This shortcoming often limits our understanding of how leadership acts on a phenomenon of interest to a single level of analysis. This article develops a computational model and describes a levels-based comparison of four types of leadership that represent three different levels: individual, dyad, and group. When examined across a dynamic group decision-making optimization scenario, group-based leadership is found to produce decisions that are closer to optimal than dyadic-based and individual-based leadership. An alternative computational model varying individual cognitive and experience-based components among group members also indicates that group-based leadership produces more optimal decisions. First published in Leadership Quarterly (Dionne, S. D., & Dionne, P. J. (2008). Levels-based leadership and hierarchical group decision optimization: A simulation. Leadership Quarterly, 19, 212–234), this version offers an updated introduction discussing simulation as a theoretical development tool and supplies additional evidence regarding the growth of simulation methods in leadership research.

This paper aims to explore the impact of a recent earthquake activity on house prices and their spatial distribution in the Istanbul housing market.

The paper uses a multi-level approach within an event study framework to model changes in the pattern of house prices in Istanbul. The model allows the isolation of the effects of earthquake risk and explores the differential impact in different submarkets in two study periods – one before (2007) and one after (2012) recent earthquake activity in the Van region, which although in Eastern Turkey served to alter the perceptions of risk through the wider geographic region.

The analysis shows that there are variations in the size of price discounts in submarkets resulting from the differential influence of a recent earthquake activity on perceived risk of damage. The model results show that the spatial impacts of these changes are not transmitted evenly across the study area. Rather it is clear that submarkets at the cheaper end of the market have proportionately larger negative impacts on real estate values.

The robustness of the models would be enhanced by the addition of further spatial levels and larger data sets.

The methods introduced in this study can be used by real estate agents, valuers and insurance companies to help them more accurately assess the likely impacts of changes in the perceived risk of earthquake activity (or other environmental events such as flooding) on the formation of house prices in different market segments.

The application of these methods is intended to inform a fairer approach to setting insurance premiums and a better basis for determining policy interventions and public investment designed to mitigate potential earthquake risk.

The paper represents an attempt to develop a novel extension of the standard use of hedonic models in event studies to investigate the impact of natural disasters on real estate values. The value of the approach is that it is able to better capture the granularity of the spatial effects of environmental events than the standard approach.

The purpose of this study is to examine how five different multi-level governance (MLG) models affect place branding (PB) performance in Saudi Arabia.

In hierarchical administrative systems, central governments exert control on PB, influencing its effectiveness. While PB as such is widely studied, the effect of MLG on PB performance in centralized administrative systems remains understudied. The study is approached as a multiple case study of nine cities.

The study reveals that different MLG models indeed affect PB performance differently. Direct access to central leadership and resources boosts branding performance, while privatization promotes flexibility with similarly positive effects. Study findings, furthermore, show that some cities are considered too big to fail. Cities such as Riyadh and Neom are of prime importance and receive plenty of resources and leadership attention, while others are considered peripheral, are under-resourced and branding performance suffers accordingly. Emerging differences in PB performance associated with different MLG models are thus likely to deepen the gap between urban economic winners and losers.

This paper introduces five MLG models based on the actors involved in PB, their interactions and their access to resources. For each model, this paper assesses other factors which may influence the effectiveness of PB as well, such as access to the national leadership and staff capacity. This research thereby adds to the literature by identifying specific factors within MLG models influencing PB performance in hierarchical administrative systems.

The purpose of this paper is to extract and validate the dimensions of service quality in retail banking services in India by adopting an integrated and hierarchical perspective of service quality determinants.

The paper empirically validates a parsimonious (multi-dimensional and multi-level) model of service quality in retail banking services in India. The analysis was conducted using structural equation modeling. A hypothesized second-order model was tested and compared with a first-order model of service quality. The dimensions were extracted through exploratory factor analysis and validated through confirmatory factor analysis.

The second-order service quality model was accepted based on parsimony as it consisted of five primary dimensions: Service delivery (describing the efficiency with which the service is provided), tangibles (the quality of physical service environment), reliability (the promise of right service being provided), core service (the attributes and features of the service product) and competence (the capability of employees and systems for providing the service). The second-order model enhances the understanding of the structure of service quality for retail banking services in India. The most important dimension was tangibles, especially the physical environment which facilitates efficient delivery of service.

The research provides support for a multi-dimensional second-order model of service quality in retail banking service in India. The results show that customers form perceptions of overall service quality which are reflected by five primary dimensions. The primary dimension of tangibles is the most influential.

Organizations need to measure and manage overall service quality perceptions to build trust and reinforce loyalty intentions among their customers. Banks need to adopt a multi-level approach to managing service quality perceptions, i.e. both at the dimensional level and organizational level.

This study would contribute to the enhancement of service quality outcomes in retail banking services in India which has a crucial role in the economic development.

The study proposes and validates a parsimonious and hierarchical model of service quality in the context of retail banking in Indian cultural context. Thus this research provides support to existing knowledge of service quality measurement and management and extends the understanding of its structure by validating the multi-level model in an emerging market context.

The process approach to multi-level organizational behavior is based on the assumption that multi-level organizational behavior is processual in nature. This article defines group and organizational processes and their representation as process frameworks. Both functional and inclusional classes of levels exist, each of which has at least five categories of levels. All ten categories are special cases of process frameworks. This article provides examples of each category level, which it uses to illustrate new models of organizational work, extended models of interdependence, a new typology of theories based on their levels of processes, and a new tool for survey research called knobby analyses. After explaining the basic idea of knobby analysis, the article briefly describes the processual theory of the organizational hologram, the use of linear programming, and causal-chain analysis to provide multi-level explanations of employee opinion data. These ideas are embodied in conducting a strategic organizational diagnosis, which is the first stage of organizational design. Organizational design encompasses multiple stages, each of which itself involves multiple, multi-level phenomena and analyses. The basic point is that the processual nature of multi-level organizational phenomena gives more hope for improvements in theory building and their application if one uses the process approach rather than a variable approach.

This chapter reviews research on multi-level organizational justice. The first half of the chapter provides the historical context for this issue, discusses organizational-level antecedents to individual-level justice perceptions (i.e., culture and organizational structure), and then focuses on the study of justice climate. A summary model depicts the justice climate findings to date and gives recommendations for future research. The second half of the chapter discusses the process of justice climate emergence. Pulling from classical bottom-up and top-down climate emergence models as well as contemporary justice theory, it outlines a theoretical model whereby individual differences and environmental characteristics interact to influence justice judgments. Through a process of information sharing, shared and unique experiences, and interactions among group members, a justice climate emerges. The chapter concludes by presenting ideas about how such a process might be empirically modeled.

The purpose of this paper is to adopt a three-stage cloud-based management system for optimizing greenhouse gases (GHG) emission and marketing decisions with supplier selection and product family design in a multi-level supply chain with multiple suppliers, one single manufacturer and multiple retailers.

The manufacturer purchases optional components of a certain functionality from his alternative suppliers and customizes a set of platform products for retailers in different independent market segments. To tackle the studied problem, a hierarchical analytical target cascading (ATC) model is proposed, Jaya algorithm is applied and supplier selection and product family design are implemented in its encoding procedure.

A case study is used to verify the effectiveness of the ATC model in solving the optimization problem and the corresponding algorithm. It has shown that the ATC model can not only obtain close optimization results as a central optimization method but also maintain the autonomous decision rights of different supply chain members.

This paper first develops a three-stage cloud-based management system to optimize GHG emission, marketing decisions, supplier selection and product family design in a multi-level supply chain. Then, the ATC model is proposed to obtain the close optimization results as central optimization method and also maintain the autonomous decision rights of different supply chain members.