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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.

This paper aims to discuss the capability of current governance models to achieve the sustainable development goals (SDGs) in the tourism sphere and propose a broad model of governance to support the SDGs agenda.

The paper reviews the existing literature and uses it as a basis for developing a model of governance. The proposed model is inspired by recent studies that discuss the implementation of the SDGs agenda in tourism and on Fennell’s (2019) framework for tourism ethics.

The study proposes a multi-level model of governance that espouses the need for a stronger supranational system that curtails the power of both governments and the private sector. It also emphasizes the need to identify hypernorms that delimit the capacity for action at the various levels and which are determined by accessing varied stakeholders’ views within this system at the international level.

This paper proposes a model of governance for the implementation of the SDGs as a foothold for future discussions. It highlights the main challenges that may be faced in the implementation of such a system and suggests several avenues for future research.

High-resolution remote sensing images possess a wealth of semantic information. However, these images often contain objects of different sizes and distributions, which make the semantic segmentation task challenging. In this paper, a bidirectional feature fusion network (BFFNet) is designed to address this challenge, which aims at increasing the accurate recognition of surface objects in order to effectively classify special features.

There are two main crucial elements in BFFNet. Firstly, the mean-weighted module (MWM) is used to obtain the key features in the main network. Secondly, the proposed polarization enhanced branch network performs feature extraction simultaneously with the main network to obtain different feature information. The authors then fuse these two features in both directions while applying a cross-entropy loss function to monitor the network training process. Finally, BFFNet is validated on two publicly available datasets, Potsdam and Vaihingen.

In this paper, a quantitative analysis method is used to illustrate that the proposed network achieves superior performance of 2–6%, respectively, compared to other mainstream segmentation networks from experimental results on two datasets. Complete ablation experiments are also conducted to demonstrate the effectiveness of the elements in the network. In summary, BFFNet has proven to be effective in achieving accurate identification of small objects and in reducing the effect of shadows on the segmentation process.

The originality of the paper is the proposal of a BFFNet based on multi-scale and multi-attention strategies to improve the ability to accurately segment high-resolution and complex remote sensing images, especially for small objects and shadow-obscured objects.

This study aims to propose a multi-level (bottom-up) analysis to build an organizational change capability (OCC) development model by integrating paradox and social cognitive theories. Using these theories, OCC (Level 2) is influenced by the leader’s paradox mindset (Level 1) and collective PsyCap (Level 2). The study also examined the moderating effect of magnitude to change on the effect of leader’s paradox mindset on OCC.

The proposed hypotheses were tested empirically using data from 327 respondents and 48 work teams from 21 leading private higher education institutions in Indonesia. To analyze the data, a multi-level analysis was conducted with Mplus software.

The results showed that, in a cross-level relationship, leader’s paradox mindset had a positive effect on OCC, whereas OCC mediated the effect of leader’s paradox mindset on organizational change performance. On an organizational level, collective PsyCap affected OCC, and OCC significantly mediated the relationship between collective PsyCap and organizational change performance. Moreover, the authors found a moderating effect of magnitude on change of leader’s paradox mindset to OCC.

This study used a multi-level analysis to evaluate the mechanisms of influence of leader’s paradox mindset (bottom-up) on OCC and the moderation effect of magnitude to change in an Indonesian context.

Since the outbreak of the COVID-19 pandemic, most organizations have experienced a sudden and unprecedented drop in revenue and productivity. However, the pandemic did not exclusively negatively impact organizations; rather, it resulted in both negative and positive effects. To delve into the multi-level process through which organizational outcomes change from negative to positive indicators, this study focuses on organizational resilience as a theoretical concept to overcome pandemic-related turmoil.

The authors conducted a multi-level analysis based on grounded theory with a sample of 30 healthcare employees who worked in hospitals and were simultaneously enrolled in a part-time master of business administration (MBA) program at a university in the Midwest. Of the 30 participants, 21 were from a single university hospital (UH), and the remaining 9 participants were from other hospitals (non-UH).

The authors analyzed the data and incorporated three existing perspectives of organizational resilience (attribute, process and multi-level views) into an integrated model. The authors identified 25 first-order concepts and 8 second-order themes and categorized them into 4 aggregate dimensions at different unit levels: organizational field, leadership, operation and individual units.

A resilient hospital operates as a cohesive system, with entities at various levels – from individuals and teams to the broader organization – collaborating seamlessly to foster resilience. Top management team (TMT) should persistently communicate with employees to provide information about the current crisis and clear strategic directions to reduce employees' fear and prevent anomie stemming from future uncertainty. Managers should not only be concerned about employees' physical safety from infection and psychological safety from isolation but also encourage employees to elicit meaningfulness from their work. Furthermore, TMT and human resource (HR) teams should adapt human resource management (HRM) practices to allow for flexibility and optimism in employee roles.

In this study, the authors utilized a qualitative methodology with grounded theory in order to develop a comprehensive model that holds theoretical, methodological and practical significance. Theoretically, the authors' novelty lies in the synthesis of three distinct perspectives: attribute, process and multi-level. The authors merged these approaches into a unified model, identifying precursors of resilience at different levels. Methodologically, the authors focused on hospitals as target samples, which were the foremost and representative organizations severely confronting the crisis and turmoil brought by the pandemic. The authors documented organizations' experiences amidst the crisis as they unfolded in real time rather than in hindsight. This approach highlights the immediacy and significance of the authors' research in the realm of crisis management. Practically, the authors' findings illuminate that organizational resilience can be developed through a collaborative effort. It emerges from coordinated interactions across various organizational actors, from employees and middle managers to the TMT.

The purpose of the study is twofold. First, it aims to analyse the impact of green human resource management (GHRM) on green employee creativity. Second, it further explores the mediating role of personal moral norms between GHRM and green employee creativity.

Through multi-source and multi-level analysis, data was collected from 46 managers and 315 employees to investigate the role of personal moral norms in GHRM and green employee creativity. For data analysis, multi-level structural equation modelling was applied using Mplus software version 8.6.

Positive and significant effects were observed between GHRM, personal moral norms and green employee creativity. However, personal moral norms partially mediated the relationship between GHRM and green employee creativity.

The study is first in itself to explore the interplay between the variables in a multi-level manner. The present study aims at addressing the urgent call by the United Nations regarding Sustainable Development Goals (SDGs) for three key SDGs, focussing on decent work and economic growth (SDG 8), boosting industry, innovation and infrastructure (SDG 9) and supporting climate action (SDG 12).

Small and medium-scale enterprises (SMEs) that operate with modest financial investments and commodities face numerous challenges to remain in business. One major philosophy used by SMEs these days is the implementation of lean manufacturing to get solutions for various issues they encounter. But is lean getting sustained over time? The purpose of this research is to design a Sustainable Lean Performance Index (SLPI) to assess the sustainability of lean systems and to pinpoint the variables that might be present as potential lean system inhibitors which hinder the sustainability of leanness.

A multi-level sustainable lean performance model is constructed and presented based on the literature research, field investigation and survey conducted by administering a questionnaire. Fuzzy logic approach is used to analyse the multi-level model.

SLPI for the SMEs is found using fuzzy logic approach. Additionally, the ranking score system is applied to categorise attributes into weak and strong categories. The performance of the current lean system is determined to be “fair” based on the Euclidean distance approach and the SLPI for SMEs.

This work is concentrated only in South India because of the country’s vast geographical area and rich and wide diversity in industrial culture of the nation. Hence, more work can be done incorporating the other parts of the country and can analyse the lean behaviour in a comparative manner.

The generalised sustainable lean model analysed using fuzzy logic identifies the inhibitors and level of performance of SMEs in South India. This can be implemented to find out the level of performance in the SMEs after a deeper study and analysis around the SMEs of the country.

The sustainable assessment of lean parameters in the SMEs of India is found to be very less in literature, and it lacks profundity. The model established in this study assesses the sustainability of the lean methodology adopted in SMEs by considering the lean and sustainability attributes along with enablers like technology, ethics, customer satisfaction and innovation with the aid of fuzzy logic.

This study seeks to explicate how institutional disruptions impact multinational corporation (MNC) subsidiary control choices. It uses institutional theory to understand the influence of formal and informal institutions across countries on the type of control system employed in an MNC manufacturing subsidiary.

This study’s sample is based on a unique dataset from five trustworthy sources. We use multi-level models to account for the hierarchical nature of the sample of 1,630 multinational subsidiaries spread across 26 host countries by firms from 21 home countries.

The institutional distance between the host and the home country has a negative relationship with strategic control. In contrast, the home country’s power distance has a positive relationship with strategic control.

Study findings indicate the need to incorporate formal and informal institutional elements in the control system’s conceptual framing and design. This notion complements existing visualizations of optimizing MNC controls through extant articulations of minimizing governance costs through organizational design choices or strategic needs.

The purpose of this study is to examine the impact of the (in)congruence between team leader self-evaluation and follower evaluation about the leader's transformation leadership (TL) on team performance, as well as the conditions under which the impact can be strengthened or weakened.

This study adopts a survey method to collect data from matched sales team leaders and sales team members in 81 teams. A multi-level polynomial regression analysis was conducted.

Team performance was higher in teams with balanced or high TL than with balanced or low TL. Among the teams with incongruence, no difference was found between leader underestimation and leader overestimation. TL congruence plays a moderating role in the relationship between team follower evaluation of TL and team performance, such that the relationship is stronger when team leader self-evaluation and follower evaluation are congruent than incongruent.

This study extends the authors' current understanding of TL literature by combining and contrasting the different perceptions of TL from both the leaders themselves and the followers towards leaders. The findings highlight the importance of congruence versus incongruence rather than just the high or low levels of follower TL evaluation. It provides a more complete understanding of the TL and team performance relationship than the traditional view that promotes a linear relationship between TL and performance.

Sharing patient health information (PHI) among hospitals has been much slower than the adoption of health record systems. This paper aims to investigate if privacy regulation (PR) or security measures (SMs) influence hospitals’ use of health information exchange (HIE) to share PHI with other providers (e.g. physicians, labs, hospitals). The study specifically focuses on how multiple PRs can impede and a strong national security infrastructure (NSI) can support HIE.

The study uses secondary data from a multi-national and multi-hospital survey administered by the European Union. The multi-level structure of the cross-sectional panel data is used to test the influence of both hospital-level (e.g. PR) and national-level variables (e.g. NSI) on HIE. A total of nine types of HIE, three types of PRs, nine SMs and other relevant control variables are considered. This study uses a two-level random intercept generalized linear model to test the hypothesis proposed in the study.

The study finds that national-level PRs (NLPR) have the strongest positive influence on HIE in comparison to regional (RLPR) and hospital-level (HLPR) PRs. Moreover, the study finds evidence that the presence of RLPR and HLPR, on average, decreases the positive impact of NLPR by 264%. The SMs also have a significant and positive impact on HIE. Adoption of an additional SM can increase the odds of engaging in a certain type of HIE between 21% and 61%. On the other hand, a strong NSI can also amplify the positive impact of SM on certain types of HIE.

This study extends prior research on the role of PRs in enabling HIE by considering the complexities brought up by adopting multiple PRs. NLPRs have the strongest impact on HIE in comparison to RLPRs or HLPRs. Moreover, public infrastructure initiatives such as those related to secure communications can also complement SMs adopted by the providers by encouraging HIE.