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This study aims to report the results of a survey of diners’ behavior during production and consumption of dining services with three objectives. The first objective is to create customer segments that represent distinct patterns of customer participation in hospitality service encounters. The second objective is to profile these identified customer segments in terms of demographics, attitudes and behaviors. The third objective is to evaluate the relationship between customer participation segments and service outcomes.

Data were collected through an online survey of American casual dining customers. The data were analyzed using principal components factor analysis, cluster analysis on the factor scores, discriminant analysis that validated the group differences among clusters and multivariate analysis of variance on the cluster variables to determine the source of differences between groups.

The evidence showed that restaurant customers can be segmented into meaningful groups according to their reported behaviors and that level of participation is related to perceived service outcomes.

The findings suggest that service providers can use customer participation segments to understand those customers’ service needs and wants. They can then design service strategies tailored to the needs of target customer groups.

This study is the first to identify distinct segments based on hospitality customers’ roles and behaviors in service delivery. This study makes a significant contribution to the hospitality marketing literature by advancing the trend to improve service quality through a non-traditional approach, that is, by building partnerships with customers.

Slot machines and other machine gaming generate between 65 percent and 90 percent of a US casino's revenue. This article aims to examine the motivations, behaviors, and preferences of slot machine customers, and to develop market segments.

The study's objectives include: understanding the demographic, gambling motivation, and gambling behavioral characteristics of slot machine players; identifying important reasons for choosing one slot machine game over another; examining player attitudes and behaviors pertaining to progressive machines; and investigating player desire for theme‐based games. This was accomplished through an online survey of slot machine players.

Profiles of slot machine players are developed and the slot players are segmented into four clusters that explain motivations and game preferences.

This article fills in some of the gaps in understanding the gambling behavior of slot players. This study can help gaming machine manufacturers design new products and features to serve existing machine gaming customers and to attract new customers. Casino and other gaming operators can use this information not only to select the right types of machines to provide on‐site, but also to develop advertising and promotions to attract and retain new and existing customers for slot machines and other types of gaming machines.

This is the first published study that segments slot machine players from a marketing perspective and identifies their preferences, behaviors, and demographic groupings.

The purpose of this paper is to analyze the characteristics of spatio-temporal dynamics and the evolution of land use change is essential for understanding and assessing the status and transition of ecosystems. Such analysis, when applied to Horqin sandy land, can also provide basic information for appropriate decision-making.

By integrating long time series Landsat imageries and geographic information system (GIS) technology, this paper explored the spatio-temporal dynamics and evolution-induced land use change of the largest sandy land in China from 1983 to 2016. Accurate and consistent land use information and land use change information was first extracted by using the maximum likelihood classifier and the post-classification change detection method, respectively. The spatio-temporal dynamics and evolution were then analyzed using three kinds of index models: the dynamic degree model to analyze the change of regional land resources, the dynamic change transfer matrix and flow direction rate to analyze the change direction, and the barycenter transfer model to analyze the spatial pattern of land use change.

The results indicated that land use in Horqin sandy land during the study period changed dramatically. Vegetation and sandy land showed fluctuating changes, cropland and construction land steadily increased, water body decreased continuously, and the spatial distribution patterns of land use were generally unbalanced. Vegetation, sandy land and cropland were transferred frequently. The amount of vegetation loss was the largest. Water body loss was 473.6 km², which accounted for 41.7 per cent of the total water body. The loss amount of construction land was only 1.0 km². Considerable differences were noted in the rate of gravity center migration among the land use types in different periods, and the overall rate of construction land migration was the smallest. Moreover, the gravity center migration rates of the water body and sandy land were relatively high and were related to the fragile ecological environment of Horqin sandy land.

The results not only confirmed the applicability and effectiveness of the combined method of remote sensing and GIS technology but also revealed notable spatio-temporal dynamics and evolution-induced land use change throughout the different time periods (1983-1990, 1990-2000, 2000-2010, 2010-2014, 2014-2016 and 1983-2016).

The purpose of this study is to examine how the lodging market and the state economy affected by Hurricane Sandy have recovered from the damages sustained. Specifically, this study examines and predicts the influence of revenue management key performance indicators (KPIs) on recovery and lodging revenue in the affected states and the states’ economies. These KPIs include average daily rate (ADR), occupancy and revenue per available room (RevPAR).

Secondary financial data were collected for the states most damaged by Hurricane Sandy. Subsequently, pooled Ordinary Least Square (OLS) regression was conducted combining time and non-time dependent variables based on the states and radius from the landfall.

The results indicate that although the lodging market and the state economies have recovered since the onslaught of Hurricane Sandy, certain KPIs still need to improve.

Managerial implications are suggested in terms of dynamic pricing, market-based recovery, the KPIs, federal aid and facility management.

Despite its importance, research on the effects of climate change in the hospitality context has not actively progressed after Hurricane Katrina. Time and non-time dependent variables are combined in this analysis to gain a richer understanding of the impacts and recovery of KPIs on the revenue in the lodging market and the revenue on states’ economies. Additional analysis based on the radius from the landfall of the hurricane was performed to examine the impact and recovery based on geographical proximity.

The purpose of our study is to investigate the effects of politically-connected boards (PCBs) on over-(under-)investment in labor. We also examine the impacts of the supervisory board (SB)’s optimal tenure on the association between PCBs and over-investment in labor.

We constructed the proxy for PCBs using a dummy variable set to 1 (one) if a firm has politically-connected boards and zero (0) otherwise. For the robustness check, we used the number of politically-connected members on the boards as the proxy for PCBs.

We find that the presence of PCBs reduces over-investment in labor. Consistent with our prediction, we found no significant association between PCBs and under-investment in labor. We also find that the SB with optimal tenure strengthens the negative association between PCBs and over-investment in labor. In our channel analysis, we find that the presence of PCB mitigates over-investment in labor through a higher dividend payout ratio.

Due to the unavailability of data in firms’ annual reports regarding the number of poorly-skilled and highly skilled employees, we were not able to examine the effect of low-skilled and high-skilled employees on over-investment in labor. Also, we were not able to examine over-(under-)investment in labor by drawing a distinction between general (generalist) and firm-specific human capital (specialist) as suggested by Sevcenko, Wu, and Kacperczyk (2022). Generally, it is more difficult for managers to hire highly-skilled employees, specialists in particular, thereby driving the choice of either over- or under-investing in the labor forces. In addition, in the firms’ annual reports, there is no information regarding temporary employees. Therefore, if and when such data become available, this would provide another avenue for future research.

Our study offers several practical implications and insights to stakeholders (e.g. insiders or management, shareholders, investors, analysts and creditors) in the following ways. First, our study highlights significant differences between capital investment and labor investment. For instance, labor investment is considered an expense rather than an asset (Wyatt, 2008) because, although such investment is human capital and is not recognized on the firm’s balance sheet (Boon et al., 2017). In addition, labor investment is characterized by: its flexibility which enables firms to make frequent adjustments (Hamermesh, 1995; Dixit & Pindyck, 2012; Aksin et al., 2015), its non-homogeneity since every employee is unique (Luo et al., 2020), its direct impact on morale and productivity of a firm (Azadegan et al., 2013; Mishina et al., 2004; Tatikonda et al., 2013), and its financial outlay which affects the ongoing cash flows of a firm (Sualihu et al., 2021; Khedmati et al., 2020; Merz & Yashiv, 2007). Second, our findings reveal that the presence of PCBs could help to reduce over-investment in labor. However, if managers of a firm choose to under-invest in labor in order to obtain better profit in the short-term through cost saving, they should be aware of the potential consequences of facing a financial loss when a new business opportunity suddenly arises which requires a larger labor force. Third, our findings help stakeholders to re-focus on the labor investment. This is crucial due to the fact that labor investment is often neglected by those stakeholders because the expenditure of labor investment is not recognized on the firm’s balance sheet as an asset. Instead, it is written off as an expense in the firm’s income statement. Fourth, our findings also provide insightful information to stakeholders, suggesting that an SB with optimal tenure is more committed to a firm, and this factor plays an important role in strengthening the negative association between PCBs and over-investment in labor.

First, our findings provide a valuable understanding of the effects of PCBs on over-(under-)investment in labor. Stakeholders could use information disclosed in the financial statements of a publicly-listed firm to determine the extent of the firm’s investment in labor and PCBs, and compare this information with similar firms in the same industry sector. Second, our findings give a better understanding of the association between investment in labor and political connections , which are human and social capital that could determine the long-term survival and success of a firm. Third, for shareholders, the appointment of board members with political connections is an important strategic decision to build political capital, which is likely to have a long-term impact on the financial performance of a firm; therefore, it requires thoughtful consultation with firm insiders.

Our findings highlight the role of PCBs in reducing over-investment in labor. These findings are significant because both investment in labor and political connections as human and social capital can play an important role in determining the long-term survival and success of a firm.

The soil water retention curve (SWRC) and unsaturated hydraulic conductivity (UHC) are crucial indices to assess hydraulic properties of porous media that primarily depend on the particle and pore size distributions. This study aims to present a method based on the discrete element model (DEM) and the typical Arya and Paris model (AP model) to numerically predict SWRC and UHC.

First, the DEM (PFC^3D software) is used to construct the pore and particle size distributions in porous media. The number of particles is calculated according to the AP model, which can be applied to evaluate the relationship between the suction head and the moisture of porous media. Subsequently, combining critical path analysis (CPA) and fractal theory, the air entry value is applied to calculate the critical pore radius (CPR) and the critical volume fraction (CVF) for evaluating the unsaturated hydraulic conductivity.

This method is validated against the experimental results of 11 soils from the clay loam to the sand, and then the scaling parameter in the AP model and critical volume fraction value for many types of soils are presented for reference; subsequently, the gradation effect on hydraulic property of soils is analyzed. Furthermore, the calculation for unbound graded aggregate (UGA) material as a special case and a theoretical extension are provided.

The presented study provides an important insight into the relationship between the heterogeneous particle and hydraulic properties by the DEM and sheds light on the directions for future study of a method to investigate the hydraulic properties of porous media.

This chapter identifies and analyzes three systemic obstacles to American public policy addressing natural disasters: symbolic obstacles, cognitive obstacles, and structural obstacles. The way we talk about natural disaster, the way we think about the risks of building in hazardous places, and structural aspects of American political institutions all favor development over restraint. These forces have such strength that in the wake of most disasters society automatically and thoughtlessly responds by rebuilding what was damaged or destroyed, even if reconstruction perpetuates disaster vulnerability. Only by addressing each of the obstacles identified are reform efforts likely to succeed.

Coastal zone ecological restoration project is of great significance to alleviate marine ecological degradation. Evaluating the effect of coastal ecological restoration projects and identifying the obstacle factors affecting their restoration level can provide an empirical basis for future Marine ecological restoration projects.

However, due to the initial stage of coastal zone ecological restoration projects, the actual monitoring data of coastal zone ecological restoration is relatively lacking. Based on the CRITIC-TOPSIS (combination of CRITIC method and TOPSIS method) method, combined with the subjective perception of the public and the actual data of the restoration project, this paper proposes an evaluation method of the coastal zone ecological restoration effect to obtain the specific implementation effect of the coastal zone ecological restoration project. The main obstacle factors affecting the evaluation of coastal ecological restoration effect are identified by using the obstacle degree model.

This paper conducted an empirical study on the restoration of sandy shoreline and coastal wetland in Qinhuangdao city. Based on the data of restoration projects and the subjective perception of ecological restoration by the public in Qinhuangdao city, the research results showed that the coastal zone ecological restoration effect of Qinhuangdao city was general. The quality of the restoration project and the public perception have an important influence on the evaluation of the restoration effect. Improving the quality of the restoration project, strengthening the public's participation in ecological restoration and allowing the public to better participate in the ecological restoration of the coastal zone can improve the effect of ecological restoration of the coastal zone in an all-round way.

The research results of this paper have a guiding role in the ecological restoration of coastal cities in the future, and also have a demonstration and reference role for the assessment of the effect of ecological restoration of coastal zones.

At a time when many people are experiencing stress, burnout, and strain at work, a relaxing vacation becomes increasingly important. Remote locations such as Bali, the Maldives, or the Caribbean have experienced a steady increase in popularity: exotic dishes, turquoise water, and white sandy beaches are often tourist magnets. While the corona crisis is changing the name of the game at this point, those destinations may attract travelers seeking remote destinations catering to the individual rather than the group. In response, new luxury resorts have emerged in recent years fostering global travel with its set of positive and negative impacts on the environment, the economy, and communities. In light of a global climate emergency, is luxury tourism in remote destinations compatible with sustainable development? This chapter, exploratory by nature, concludes that if there is one hope, it is that sustainability becomes the sine qua non of luxury tourism in the near, post-corona future.

Wheel‐terrain interaction has hardly been taken into consideration in the process of conventional mobile robot design, but its importance has been reflected increasingly towards these categories of mobile robots in rough sandy terrain or obstacle‐dense ground, as the first performance index in this situation is the trafficability of robot whose propulsion is uniquely generated by wheel‐terrain interaction. Consequently, it is valuable to find an optimized design method when the terrain and robot itself are regarded simultaneously. The purpose of this paper is to present a novel and reasonable design approach to mobile robot in sandy terrain.

Leading to some conflicted performance indices of robot, terramechanics describes the non‐linear characteristics in wheel‐terrain interaction mathematically, therefore, trade‐offs must be implemented to get a proper solution by multi‐objective optimization (MOO). In this paper, a five‐wheeled drive and five‐wheeled steering (5WD5WS) reconfigurable mobile robot is taken as demonstration with taxonomy of total‐symmetrical, partial‐symmetrical and asymmetrical prototypes. After function modeling, the MOO is carried out via iSIGHT‐FD using NCGA (Neighborhood Cultivation Genetic Algorithm) to minimize the mass, wheel resistance and maximize the static stability simultaneously.

After MOO, a compact and light weighted asymmetrical prototype is obtained with better trafficability, and other prototypes can produce diversified configurations to meet specific requirements. Significantly reduced masses (about 17 kg) enhance the grade‐ability when robot is in rough terrain. Performed real‐world experiments have also verified these prototypes.

The paper presents a new design approach for a mobile robot which focuses on both robot and terrain simultaneously with respect to conflicted factors. To unveil the insight relation of these factors, MOO is an effective tool to get a trade‐offs prototype.