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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).

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 use of multi-level labels can enhance product visibility by enabling labeling of various items. Moreover, it can better accommodate the diversity on both the producer and consumer sides. However, studies on the willingness to pay (WTP) for premium levels of those animal welfare labels are scarce.

We investigate consumers’ WTP for a four-level animal husbandry label introduced to the market by German retailers in 2019 by conducting an online survey with 1,223 German meat consumers using Van Westendorp’s price sensitivity meter (PSM).

There is a significant increase in WTP for level 3 of the husbandry label, but only a slight increase for level 4. One explanation is that consumers may have the mistaken belief that level 3 already includes outdoor access for animals. As a result of this expectation, consumers may not perceive much added value in level 4, which is reflected in their reluctance to pay a higher price. This is reinforced by the finding that once informed of the criteria, 18% of the participants reduced their WTP for level 3, whereas only 6% considered a discount for level 4. Furthermore, 40% were prepared to pay more for level 4 after being informed of the respective criteria than they had previously stated.

To the best of our knowledge, this study is the first to analyze and emphasize the importance of clear label communication, particularly for multi-level animal husbandry labels.

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.

Digital platforms (DP) are transforming service delivery and affecting associated actors. The position of DPs is impacted by the regulations. However, emerging economies often lack the regulatory environment to support DPs. This paper aims to explore the regulatory developments for DPs using the multi-level perspective (MLP).

The paper explores regulatory developments of ride-hailing platforms (RHPs) in India and their impacts. This study uses qualitative interview data from platform representatives, bureaucrats, drivers, experts and policy documents.

Regulatory developments in the ride-hailing space cannot be explained as a linear progression. The static institutional assumptions, especially without considering the multi-actors and multi-levels in policy formulation, do not serve associated actors adequately in different times and spaces. The RHPs regulations must consider the perspective of new RHPs and the support available to them. Non-consideration of short- and long-term perspectives of RHPs may have unequal outcomes for established and new RHPs.

This research has implications for the digital economy regulatory ecosystem, DPs and implications for policymakers. Though the data from legal documents and qualitative interviews is adequate, transactional data from the RHPs and interviews with judiciary actors would have been insightful.

The study provides insights into critical aspects of regulatory evolution, governance and regulatory impact on the DPs’ ecosystem. The right balance of regulations according to the business models of DPs allows DPs to have space for growth and development of the platform ecosystem.

This research shows the interactions in the digital space and how regulations can impact various actors. A balanced policy can guide the paths of DPs to have equal opportunities.

DP regulations have a complex structure. The paper studies regulatory developments of DPs and the impacts of governance and controls on associated players and platform ecosystems.

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.

This study aims to further the understanding of multi-level analysis in inter-organisational relationships by investigating the interplay of governance, cooperation and coordination in inter-organisational projects (IOPs) on sub-system and project levels.

The authors use the Viable Systems Model as a framework to analyse inter-organisational project governance, cooperation and coordination by adopting a multiple-case study.

The findings illustrate how governance and coordination mechanisms exhibit a filter-down effect on lower sub-systems while cooperation influence is confined within each sub-system. While remarking the importance of specific sub-systems on the overall project performance, the interplay of governance, cooperation and coordination across sub-systems appears to be complex, with governance influencing cooperation and coordination, whereas cooperation and coordination influence each other with an incremental effect.

This study defines two propositions that explain how multiple levels of analysis (project and sub-systems) can support the governance of large inter-organisational projects. The authors elaborate theory on the interplay of inter-organisational project governance, cooperation and coordination.

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.

While previous studies have proved the significance of family firm innovativeness (FFI), the question of how the emotion-regulation capabilities of family business managers affect FFI still remains open. This paper aims to examine the impact of the emotion-regulation capabilities of family business managers on FFI moderated by the family involvement in business management.

The present study is based on a quantitative research design. Data were collected with the help of a telephone survey. Overall, 192 family firms were surveyed, and the results were analysed using structural equation modelling (SEM).

The findings indicate that managers' emotion-regulation capabilities (independent variable) positively impact FFI (dependent variable). The research results also indicate that having more family members involved in the business (moderating variable) can lead to better innovation outcomes, assuming these family managers have sufficient emotion-regulating capabilities.

The research context could be broadened by differentiating between the industries in which family firms operate. This could aid a better understanding of the challenges, opportunities and market trends in different sectors. Future research might also include more diverse countries with deep family business traditions, strengthening the robustness of the findings across more varied contexts.

Using a multi-level perspective, this study contributes to the dynamic managerial capabilities and family business literature by showing that, in an environment where familial relationships can affect working relationships, the ability of managers to control their emotions and others' emotions can be a critical managerial resource that impacts FFI.

We studied the relationship between job engagement and systematic problem solving (SPS) among shop-floor employees and how lean production (LP) and Internet of Things (IoT) systems moderate this relationship.

We collected data from a sample of 440 shop floor workers in 101 manufacturing work units across 33 plants. Because our data is nested, we employed a series of multilevel regression models to test the hypotheses. The application of IoT systems within work units was evaluated by our research team through direct observations from on-site visits.

Our findings indicate a positive association between job engagement and SPS. Additionally, we found that the adoption of lean bundles positively moderates this relationship, while, surprisingly, the adoption of IoT systems negatively moderates this relationship. Interestingly, we found that, when the adoption of IoT systems is complemented by a lean management system, workers tend to experience a higher effect on the SPS of their engagement.

One limitation of this research is the reliance on the self-reported data collected from both workers (job engagement, SPS and control variables) and supervisors (lean bundles). Furthermore, our study was conducted in a specific country, Italy, which might have limitations on the generalizability of the results since cross-cultural differences in job engagement and SPS have been documented.

Our findings highlight that employees’ strong engagement in SPS behaviors is shaped by the managerial and technological systems implemented on the shop floor. Specifically, we point out that implementing IoT systems without the appropriate managerial practices can pose challenges to fostering employee engagement and SPS.

This paper provides new insights on how lean and new technologies contribute to the development of learning-to-learn capabilities at the individual level by empirically analyzing the moderating effects of IoT systems and LP on the relationship between job engagement and SPS.