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This study aims to investigate the effect of organizational ambidexterity (OA) and organizational green culture (OGC) on corporate sustainability (CS) while incorporating the mediating role of green innovation (GI) to provide a detailed insight into CS. The study also presents a research framework based on the Organizational Ambidexterity theory and Natural Resource-based view to explain the factors contributing to CS.

Using stratified sampling, the study collected data through survey-based empirical research from 307 textile companies registered with the Securities and Exchange Commission of Pakistan (SECP) or the All-Pakistan Textile Mills Association (APTMA). The collected data were analysed using path analysis, mediation analysis and moderation analysis through smart PLS-SEM version 4.0 to assess the composition and causal association of factors.

The study found a significant relationship between OA and OGC with CS. Furthermore, the study revealed that green innovation partially mediates the relationship between OGC and CS. The proposed research framework can be valuable for promoting and recommending actions to enhance CS.

The study on CS in the textile sector of Pakistan has limitations such as a narrow focus, cross-sectional design and reliance on self-reported data. Future research should explore additional factors, conduct longitudinal research, investigate contextual factors, scrutinize specific green innovation practices and broaden the scope of the study to include SMEs and other textile organizations.

The research framework can help senior executives to foster CS by promoting OGC, OA and GI. Practitioners and academicians can also utilize or further investigate the proposed framework for validation and to foster CS.

This study fills gaps in the existing literature by investigating the mediating effect of GI between OGC and CS. The proposed research framework provides a comprehensive understanding of the factors contributing to CS based on the Organizational Ambidexterity theory and Natural Resource-based view.

This paper aims to study the feasibility of proposed method to focus the electroporation ablation by mean of multi-output multi-electrode system.

The proposed method has been developed based on a previously designed electroporation system, which has the capabilities to modify the electric field distribution in real time, and to estimate the impedance distribution. Taking into consideration the features of the system and biological tissues, the problem has been addressed in three phases: modeling, control system design and simulation testing. In the first phase, a finite element analysis model has been proposed to reproduce the electric field distribution within the hepatic tissue, based on the characteristics of the electroporation system. Then, a control strategy has been proposed with the goal of ensuring complete ablation while minimizing the affected volume of healthy tissue. Finally, to check the feasibility of the proposal, several representative cases have been simulated, and the results have been compared with those obtained by a traditional system.

The proposed method achieves the proposed goal, as part of a complex electroporation system designed to improve the targeting, effectiveness and control of electroporation treatments and serve to demonstrate the feasibility of developing new electroporation systems capable of adapting to changes in the preplanning of the treatment in real-time.

The work presents a thorough study of control method to multi-output multi-electrode electroporation system by mean of a rigorous numerical simulation.

Existing deterministic models that predict the capacity of corroded reinforced concrete (RC) beams have limited applicability because they were based on accelerated tests that induce general corrosion. This research gap was addressed by performing a combined numerical and statistical analysis on RC beams, subjected to natural corrosion, to achieve a much better forecast.

Data of 42 naturally corroded beams were collected from the literature and analyzed numerically. Four constitutive models and their combinations were considered: the elastic-semi-plastic and elastic-perfectly-plastic models for steel, and two tensile models for concrete with and without the post-cracking stresses. Meanwhile, Popovics’ model was used to describe the behavior of concrete under compression. Corrosion coefficients were developed as functions of corrosion degree and beam parameters through linear regression analysis to fit the theoretical moment capacities with test data. The performance of the coefficients derived from different combinations of constitutive laws was then compared and validated.

The results showed that the highest accuracy (R² = 0.90) was achieved when the tensile response of concrete was modeled without the residual stresses after cracking and the steel was analyzed as an elastic-perfectly-plastic material. The proposed procedure and regression model also showed reasonable agreement with experimental data, even performing better than the current models derived from accelerated tests and traditional procedures.

This study presents a simple but reliable approach for quantifying the capacity of RC beams under more realistic conditions than previously reported. This method is simple and requires only a few variables to be employed. Civil engineers can use it to obtain a quick and rough estimate of the structural condition of corroding RC beams.

The seasonality in the behavior of travelers is something that goes back to the origin of the trips themselves. This seasonality is due to multiple factors, some easy to counteract and others difficult to solve. But, regardless of the causes, it is a phenomenon that generates significant negative impacts on society and the environment in which the phenomenon of tourist seasonality occurs. All tourist destinations have seasonality, but in some cases, it is very high and in others it has a minimal incidence. The objective of this chapter is to ponder the impacts and consequences of seasonality in regions with a strong tourism development, allowing to put into context the aspects of society impacted by this phenomenon and the positive implications that the reduction of seasonality would have. For this, an analysis of a theoretical model with two regions in opposite situations is carried out, raising the possible effects of a high seasonality. The cases of the Balearic Islands and the Canary Islands are also reviewed, as real examples of the regional typologies taken into consideration in the theoretical model. This seeks to ponder the problems attributable to seasonality. As a final reflection, the enormous typology of negative impacts generated and the need to continue analyzing the seasonality and its impacts are emphasized.

Social enterprises (SEs), part of the third sector, are hybrid organizations combining the pursuit of social scopes with commercial business solutions. In seeking for social value, they pair for-profit and non-profit features, thereby compensating for shortcomings of both the public sector and the commercial market. Therefore, the performance management of such organizations assumes a crucial relevance. Among the available tools, the balanced scorecard (BSC) aims to capture performance multidimensionality, at the same time fostering legitimacy towards stakeholders.

In general terms, the BSC has the limit to follow a linear and static logic of construction and functioning. For this reason, scholars combine it with system dynamics (SD) to create dynamic balanced scorecards (DBSCs). However, literature seems to devote scarce attention to the adoption of such analytic tools in the third sector, particularly in SEs. This chapter wants to contribute to bridging this gap by proposing a tailored application in the context of a social cooperative, active in the clothing recycle and in the re-integration of disadvantaged social categories. By referring to previous literature about DBSC, two modelling strategies are identified: the BSC-driven and the SD-driven. The latter, based on inductive reasoning, is the one privileged for the study because of its wider flexibility. The modelling outputs consider different perspectives than the ones within traditional BSCs, contain elements of circular causality and show how financial and non-financial performances interplay and co-determine each other. Insights from the proposed model can be useful to support both decision-making and stakeholder engagement.

This study aims to understand the motivations behind using Airbnb as a collaborative housing platform brand, their impact on satisfaction and engagement, and how the latter affects brand electronic Word of Mouth (eWOM) and brand loyalty. It also analyzes the potential moderating effect of the use intensity of collaborative housing platforms for the proposed causal relationships.

An online survey was addressed to active users of Airbnb with a final sample of 405 users. Data were analyzed using a covariance-based structural equation modeling (SEM) to test the causal model and a multigroup SEM to test the moderator effect of the intensity of use.

The results show that convenience affects brand satisfaction and hedonic motivation influences brand engagement, and both affect return intention and eWOM. In contrast, sustainability motivations seem unrelated both with satisfaction and engagement. Furthermore, the mechanism by which people reach loyalty in terms of return intention varies according to their usage intensity. Thus, the engagement–intention way is stronger for more intensive brand users. In contrast, the satisfaction–intention mechanism is significantly stronger for those with more sporadic use.

The management of collaborative housing platforms should promote tools and actions that favor enjoyment and fun since they increase engagement. On the other hand, it should be interesting to communicate the idea of the convenience of the applications, such as availability for a great offer, ease of contracting, or saving time, since this type of motivation directly correlates with customer satisfaction.

The motivational and behavioral heterogeneity demonstrated in this research can make it easier for people to be reached through different communication strategies and arguments both by the collaborative housing platforms and by public agencies with interests in city tourism management.

A pronounced rise in postpandemic immigration is creating consumption opportunities and challenges for countries worldwide. Past research has shown that immigrant homeownership indicates advanced consumer acculturation. However, critical factors which differentiate immigrant decisions to purchase a home remain underexplored. This study aims to examine the importance of different identity resources in determining homeownership gaps between immigrant groups in Spain during a dynamic decade.

A mixed methods research design with triangulation was used. First, the critical “historical research method” is used to empirically assess 15,465 household-level microdata files from the National Immigrant Survey of Spain. Second, the analysis is corroborated through informant interviews, an evaluation of digital news archives and other historical traces such as relevant advertisements in Spain from 2000 to 2009.

Results provided an account of immigrant homeownership whereby foreign-born consumers leveraged resources to promote social identities aligned with an advanced level of acculturation through housing investment during this period. Furthermore, marketing focused on specific targets of ethnic minority consumers coupled with government policies to promote immigrant homeownership reinforced the “Spanish Dream” as a new paradigm for housing market integration.

Spain provides an unprecedented historical context to explain marketing-related phenomena due to a perfect storm of immigration, job availability and integration supports. Contrary to popular wisdom, immigrant consumer homeownership gaps are not solely a result of differences in income and economic mobility, but rather an advanced acculturation outcome driven by personal and social investments in resources that lead to consumer identities.

The efficient functioning of the labour market is an important factor that affects long-term economic growth. The interaction of supply and demand on the labour market is influenced by institutions which change the motivations and behaviour of economic actors and, ultimately, the flexibility of the labour market. There is no consensus in the literature on the effect these institutions have on labour market outcomes. This chapter focuses on a set of selective labour market institutions (employment protection legislation, minimum wages, unemployment benefits, labour taxation, trade unions and active labour market policies), compares their relevance to other European Union (EU) countries and through the lens of the Beveridge curve it tries to evaluate their impact on effectiveness of the Czech labour market. The international comparison shows that most of the considered institutions/regulations do not reach such importance (except employment protection legislation) and that they have a significant negative effect on labour market outcomes. Even the model of the Beveridge curve does not indicate that the Czech labour market is characterised by rigidities that would impair the effectiveness of a matching process at the aggregate level.

In recent years, tourists have been progressively increasing their interest in the natural environment and its enjoyment. The objective of this study was: (1) identify the underlying variables or motivational dimensions in ecotourism; and (2) analyze the demand segmentation in ecotourism.

The empirical analysis was carried out in “Puntilla de Santa Elena” Fauna Production Reserve in Ecuador. The sample consisted of 369 surveys obtained in situ. For the data analysis, a factor analysis and a nonhierarchical K-media segmentation were performed.

The results show six motivational dimensions in ecotourism: “Self-development and Interpersonal relationships,” “Building personal relationships,” “Escape and ego-defensive function,” “Marine nature,” “Terrestrial nature” and “Rewards.” Also, according to their motivations, three segments of ecotourists emerged: “Reward and escape,” “Marine nature” and “Multiple motives.”

The limitation is the temporality with which the study was carried out. Another limitation was the number of the samples used. As future lines of research, it is proposed to investigate the offer related to ecotourism products and services adapted to the demand segments found.

Among the practical implications, operators and companies linked to the tourism sector can plan more efficient strategies, adapted to the specific needs of each segment to improve the satisfaction of tourists and the intentions of returning to the destination, providing greater benefit to the tourists, to the sustainable development of the destination and the community.

The findings of this research can help public institutions and private companies to improve the tourism supply, create sustainable plans and potentially develop more efficient marketing planning. Protected areas will benefit from information about demand. The communities will be able to elaborate products according to the motivations and found segments. Administrators will be able to create sustainable management plans for ecotourism.

As ecotourism grows, it is vital to understand the ecotourists' motivations and segmentation to improve each segment service offering. This study presents original results of the motivations and segmentation of the demand for ecotourism based on a reserve area for the production of coastal marine fauna. To obtain valid results, a study was carried out in Ecuador, this being a country with a great variety of flora and fauna ideal for ecotourism.

The purpose of this paper is to explore the significance impact of air quality as a contributing factor on residential property rents by applying geo-informatics to economic issues. Since air pollution poses a severe health threat, city residents should have a right to know about the (invisible) hazards they are exposed to.

Within spatial-temporal modeling of air pollutants in Berlin, Germany, three interpolation techniques are tested. The most suitable one is selected to create seasonal maps for 2018 and 2021 with pollution concentrations for particulate matter values and nitrogen dioxide for each 1,000 m² cell within the administrative boundaries. Based on the evaluated pollution particulate matter values, which are used as additional variables for semi-parametric regressions the impact of the air quality on rents is estimated.

The findings reveal a compelling association between air quality and the economic aspect of the residential real estate market, with noteworthy implications for both tenants and property investors. The relationship between air pollution variables and rents is statistically significant. However, there is only a “willingness-to- pay” for low particulate matter values, but not for nitrogen dioxide concentrations. With good air quality, residents in Berlin are willing to pay a higher rent (3%).

These results suggest that a “marginal willingness-to-pay” occurs in a German city. The research underscores the multifaceted impact of air quality on the residential rental market in Berlin. The evidence supports the notion that a cleaner environment not only benefits human health and the planet but also contributes significantly to the economic bottom line of property investors.

The paper has a unique data engineering approach. It collects spatiotemporal data from network of state-certified measuring sites to create an index of air pollution. This spatial information is merged with residential listings. Afterward non-linear regression models are estimated.