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This paper aims to develop a house price forecasting model to investigate the impact of neighbourhood effect on property value.

Multi-level modelling (MLM) method is used to develop the house price forecasting models. The neighbourhood effects, that is, socio-economic conditions that exist in various locations, are included in this study. Data from the local government area in Greater Sydney, Australia, has been collected to test the developed model.

Results show that the multi-level models can account for the neighbourhood effects and provide accurate forecasting results.

It is believed that the impacts on specific households may be different because of the price differences in various geographic areas. The “neighbourhood” is an important consideration in housing purchase decisions.

While increasing housing supply provisions to match the housing demand, governments may consider improving the quality of neighbourhood conditions such as transportation, surrounding environment and public space security.

The demand and supply of housing in different locations have not behaved uniformly over time, that is, they demonstrate spatial heterogeneity. The use of MLM extends the standard hedonic model to incorporate physical characteristics and socio-economic variables to estimate dwelling prices.

Industrial organizations often face difficulties in finding out the methods to meet ever increasing customer expectations and to remain competitive in the global market while maintaining controllable expenses. An effective and efficient green supply chain management (GSCM) can provide a competitive edge to the business. This paper focusses on the selection of green suppliers while simultaneously balancing economic, environmental and social issues.

In this study, it is assumed that two types of decision-makers (DMs), namely, the first level and second-level DMs operate at two separate groups in GSC. The first-level DMs always empathise to optimize carbon emissions, per unit energy consumption per product and per unit waste production, while the second-level DMs seek to optimize ordering costs, number of rejected units and number of late delivered units in the entire GSCM. In this paper, fuzzy goal programming (FGP) approach has been adopted to obtain compromise solution of the formulated problem by attaining the uppermost degree of each membership goal while reducing their deviational variables. Furthermore, demand has also been forecasted using exponential smoothing analysis. The model is verified on a real-time industrial case study.

This research enables DMs to analyse uncertainty scenarios in GSCM when information about different parameters are not known precisely.

The proposed model is restricted to vagueness only, however, DMs may need to consider probabilistic multi-choice scenarios also.

The proposed model is generic and can be applied for large-scale GSC environments with little modifications.

No prior attempt is made till date to present interval type-2 fuzzy sets in a multi-objective GSC environment where the DMs are at hierarchical levels. Interval type-2 fuzzy sets are considered as better ways to represent inconsistencies of human judgements, its incompleteness and imprecision more accurately and objectively. Also, crisp or deterministic forms of uncertain parameters have been obtained by taking expected value of the fuzzy parameters.

Facing the aging workforce but older workers’ vulnerability in the labor market, this chapter empirically explores factors and policy implications to enhance older workers’ entered employment rates (EER) after exiting the national workforce program. After reviewing older workers’ attributes and the unique methods to train them, the chapter examines demographic, socioeconomic, and program attributions to older workers’ EER, controlling for cyclical changes in the labor market. The chapter relies on three sets of models including logistic regression, multi-level mixed-effect regression, and multilevel mixed effect logistic regression models, as well as longitudinal Workforce Investment Act Standardized Record Data and Bureau of Labor Statistics unemployment data. Older dislocated workers and older adults are examined separately. Some Workforce Innovation and Opportunity Act training and related service combinations are identified to contribute to older adults and older dislocated workers’ EER and to inform strategic decision-making about future allocations of funds and policy efforts to serve older workers.

The upper-echelons model of Hambrick and Mason ((1984). Academy of Management Review, 9, 193–206) launched a new area of research and provided the first overall theoretical framework for use in understanding how the experiences, backgrounds, and values of senior executives in organizations can influence the decisions that they make. The model is typically assumed to be what Rousseau ((1985). In: B. M. Staw, & L. L. Cumming (Eds), Research in organizational behavior (Vol. 7, pp. 1–37). Greenwich, CT: JAI Press) calls “multi-level,” as it describes how both individuals and top management teams (TMTs) make decisions in line with their preferences, biases, and values; the same model is applicable to both individuals and groups. However, the levels issues in the model have never been subjected to rigorous analysis. This chapter juxtaposes levels concepts and theories on the upper-echelons model, in an effort to highlight its strengths as well as its weaknesses. While the majority of researchers use the model to describe team-level decision making, the analysis presented here reveals that the model is inherently individual-level in focus, and several important limitations must be overcome before the model will provide a full explanation of team-level decision making.

This paper aims to examine multiple learning cycles across a UK housebuilder organization following changes made to their quality management routine at the organizational level, through to subsequent understanding and enactment at the level of the individuals involved.

This study uses a qualitative case study methodology based on an analysis of six-weeks of participant observation, semi-structured ethnographic interviews and documentation within three of the organization’s regional offices. Through an abductive process, it draws on gathered data and extant literature to develop a multi-level learning model.

Four levels of learning cycles are observed within the model: individual, team (within which inter-organizational relationships nest), region and organization. Three inter-related factors are identified as influencing feed-forward and feedback across the levels: time, communication and trust. The impact of these levels and factors on the process of learning is conceptualized through the metaphor of coupling and decoupling and discussed using examples from housing development projects.

While previous models of organizational learning highlight important multi-level interaction effects, they do not explore how the different levels of learning synchronize over time for learning to move between them. This paper addresses this gap by shedding important light on how layers of learning synchronize and why and when this can occur within multi-level organizations.

The paper introduces a multi-level model to reduce prejudice through supporting diversity, equity, and inclusion (DEI) at the institutional, organizational, and individual levels. The purpose of the model is to provide theoretically undergirded pathways to explain how societal events calling for systemic changes in DEI practices can engage and inculcate such systemic changes in organizations and institutions.

The model draws upon macro-level (i.e. institutional theory and institutional logics) theories from sociology and strategic management, meso-level theories from leadership and strategy, and micro-level organizational behavior and human resource management theories.

Resting on open systems theory (Katz and Kahn, 1966) as a backdrop, the authors address how institutional changes result in organizational level changes driving multi-level outcomes of increased DEI, reduced prejudice in work-related settings, and performance gains. The authors suggest the recursive nature of the model can trigger institutional level shifts in logics or result in isomorphic pressures that further change organizational fields and organizations.

The contribution rests in a multi-level examination to help understand how environmental pressures can motivate organizations to enact broader changes related to social justice, specifically increasing efforts in DEI inside the operational aspects of the organization. By enacting these changes, the authors suggest the resultant positive changes in organizations will enhance culture and performance, creating isomorphic pressure for industry wide changes that may begin to move the needle on addressing systemic problems that feed prejudicial behavior in the workplace.

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 establish a maturity evaluation model for the application of construction steel structure welding robotics suitable for the actual situation and specific characteristics of engineering projects in China and then to assess the maturity level of the technology in the application of domestic engineering projects more scientifically.

The research follows a qualitative and quantitative analysis method. In the first stage, the structure of the maturity model is constructed and the evaluation index system is designed by using the ideas of the capability maturity model and WSR methodology for reference. In the second stage, the design of the evaluation process and the selection of evaluation methods (analytic hierarchy process method, multi-level gray comprehensive evaluation method). In the third stage, the data are collected and organized (preparation of questionnaires, distribution of questionnaires, questionnaire collection). In the fourth stage, the established maturity evaluation model is used to analyze the data.

The evaluation model established by using multi-level gray theory can effectively transform various complex indicators into an intuitive maturity level or score status. The conclusion shows that the application maturity of building steel structure welding robot technology in this project is at the development level as a whole. The maturity levels of “WuLi – ShiLi – RenLi” are respectively: development level, development level, between starting level and development level. Comparison of maturity evaluation values of five important factors (from high to low): environmental factors, technical factors, management factors, benefit factors, personnel and group factors.

In this paper, based on the existing research related to construction steel structure welding robot technology, a quantitative and holistic evaluation of the application of construction steel structure welding robot technology in domestic engineering projects is conducted for the first time from a project perspective by designing a maturity evaluation index system and establishing a maturity evaluation model. This research will help the project team to evaluate the application level (maturity) of the welding robot in the actual project, identify the shortcomings and defects of the application of this technology, then improve the weak links pertinently, and finally realize the gradual improvement of the overall application level of welding robot technology for building steel structure.

This study examines the effects of a family's and individual children's characteristics on the probability of having a divorce. Current research shows a clear indication of increased divorce risks if an individual's parents or siblings have experienced a divorce. Explanations include both shared family characteristics (including genetic effects) and common characteristics of the individual children involved. This study analyzes the effects of shared family background characteristics on the divorce risk of individuals. By analyzing siblings within families and including individual children's characteristics in the analysis, it is possible to separate individual-level and family-level effects.

In addition to employing a multi-level structure of individual siblings nested within families, the data cited here are censored. For all individuals, the length of the marriage and the divorce status are known, but the divorce status is interpreted differently for individuals who have or have not experienced divorce. For divorced individuals, the final divorce status is known; for individuals who have not experienced divorce, the final marriage status is unknown or censored. The proper analysis model for such data is event history (also called survival) analysis. This study therefore employs a multi-level event history model.

Our results show that there is a similarity in the divorce risks of siblings from the same family, which is not explained away by the available child and family characteristics. This finding suggests that shared genetic and social heritage play an important role in the intergenerational transmission of divorce risks.

The purpose of this paper is to empirically explore the underlying mechanisms through which empowerment affects organizational outcomes via a multi-dimensional model. Specifically, the paper suggests that empowerment climate (EC) is positively related to psychological empowerment (PE) and the effect of PE on the outcome variable of job satisfaction is mediated by justice perceptions and role clarity.

In total, 765 employees at the executive level across 26 distinct groups in a large manufacturing firm participated in the survey. Multi-level analyses based on both hierarchical linear modeling and multi-level structural equation modeling techniques were utilized to test the hypotheses.

This research demonstrated that EC significantly affected PE and that perceptions of justice and role clarity mediated the relationship between PE and job satisfaction. Additional analyses demonstrated that EC did not significantly affect organizational outcomes above and beyond PE, justice, and role clarity.

The current study suggests that managers concerned with increasing employee perceptions of justice may be able to do so by increasing perceptions of employee empowerment. As only individual employee perceptions of empowerment related directly to organizational outcomes, this demonstrates the importance for managers to understand perceptions of employees.

Exploring these mechanisms will strengthen the knowledge regarding how empowerment works to enhance organizational effectiveness. This will enable practitioners to better determine how and when empowerment will be most effective.