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This study aims to analyze communication from the perspective of social marketing, positive emotions, and the topics chosen by Spanish tourist destinations to show their destination image. Additionally, this research shows a message classification model, based on the aforementioned characteristics, that has generated a greater impact, offering clarity to tourism managers on the type of content they should publish to achieve greater visibility.

The methodology used in this work combines content analysis and data mining techniques. The classification tree using the chi-square automatic interaction detector (CHAID) algorithm was selected to determine predictors of like behaviour.

The results show that the predictor variables have been emotions, social marketing and topics. Also, the characteristics of the messages most likely to have a high impact are those related to emotions of joy or happiness, their purpose is behavioural, and they talk about rural, cultural issues, special dates, getaways, or highlights of a town or city for something specific.

This study is the first to analyze the content of the tweets shared by destination tourism managers from a social marketing, positive emotions, and sustainability perspective, determining the possible predictors of likes on Twitter. The authors contribute to the literature by deepening the understanding of how social marketing and the positive emotions promoted drive a more significant impact in tourism communication campaigns on social media. The authors provide destination managers with a way better to understand the variables relevant to users in tourism content.

This study introduces an ecological framework for disabilities meant to provide a new model of viewing and learning about disabilities and special education. This model projects a multi-systemic view of factors that influence a person's life, where people with disabilities are active actors in the development of the world. The increased awareness about interconnectedness, globalization, inter- and trans-disciplinarity, influences on human experience, greening, sustainability, inequality, inequity and lack of opportunities is shifting how people think about potential and growth.

The methodological approach is qualitative, interpretive research.

In disability studies, the Ecological Model of Disabilities helps reframe this uniqueness as part of the spectrum of human experiences. In special education, the Ecoducation Model helps reframe the learning experience.

This research is conceptual, but it is also all-inclusive, rendering itself to a wide application in educational settings.

The Ecoducation Model for Special Education is specific to the education of children and adults with disabilities, and it is directly compatible with the broader Ecological Model of Disabilities. These ecological models can be applied to all levels of the ecological system, and to different ecodemes of population. Nevertheless, the ecological models need to be locally implemented, with general principles tailored to national traditions, laws and resources.

Advocating for the pursuit of individual well-being within the larger society, both models call for practical changes in a multitude of areas, including legislation and policy, training of professional personnel, sufficient financial input in programs designed for the care of children and adults with disabilities, change in societal mentalities to fight discrimination, disempowerment and isolation. Because the scope of ecological frameworks is incommensurate, being both interdisciplinary and transdisciplinary, further research possibilities are countless. The ecological perspective opens the fields of disability studies and special education to new theoretical and empirical possibilities.

Two epistemological models are described as new frameworks in disability studies: the Ecological Model of Disabilities and the Ecoducation Model for Special Education. Both are original models that look into the education and inclusion of the person with disabilities.

Environmentally-friendly certifications have increased over the past decade within food supply chains. Although a large body of literature has explored the drivers leading firms to adopt such certifications, it has not closely examined the strategic motivations associated with their adoption. This paper aims to investigate an environmentally-friendly certification, VIVA, examining its role as an alternative form of supply chain governance. The aim is to investigate the drivers affecting the adoption of VIVA and to assess managerial perceptions related to transaction-related characteristics and the firm’s internal resources and capabilities.

This study draws upon both an extended transaction cost economics perspective, which is based on transaction risks and the resource-based view, which examines a firm’s internal resources. A survey was conducted via a structured questionnaire sent to all of the wine producers in charge of the decision regarding whether to adopt VIVA certification. A Hierarchal Bayesian Model was applied to analyse questionnaire responses. Such a model allows us to specify the probabilistic relationship between questions and latent constructs and to carry over uncertainty across modelling levels.

The adoption of this environmentally-friendly certification is envisioned as a tool to curb internal risks, and thus to manage behavioural uncertainty within the supply chain. A high level of exposure to exogenous transaction risks discourages firms from adopting VIVA certification. The certification system is not perceived as a promoter of operational capabilities. Managers are more likely to implement the certification when they expect that its adoption will leverage their potential knowledge of the supply chain or prompt new and better collaborations with the suppliers. Therefore, the certification can become a resource that interacts with the capabilities of the firm, expressing complementarities that stimulate the formation of dynamic capabilities.

The identification of drivers from the two theoretical perspectives offers insights into the attributes that are perceived as important by managers and which, therefore, could be leveraged to foster the adoption of the environmental certification. The external validity of the study could be improved by extending the sample to other certifications and supply chains.

The study offers a different perspective on environmental certification. It demonstrates that considering the certification as an alternative form of supply chain governance opens up a set of efficiency and strategic considerations that could be addressed to promote the effectiveness of an environmental strategy within a supply chain

Firms increasingly rely on both external and internal crowdsourcing to capture ideas more broadly and enhance innovative problem-solving. Especially in internal crowdsourcing, knowledge sharing that contributes to develop or further the understanding of the problem the idea is focused on solving can take place between critical employees, and in that way improve ideas generated by others. This far, most crowdsourcing practices have focused on identifying solutions to proposed problems, whereas much less is known about how crowds can be used to share problem-related knowledge. There is thus an untapped potential in leveraging crowds not just to generate solution-oriented ideas but also to share knowledge to improve ideas and even to reframe problems. This paper aims to explore the effect of problem- and solution-related knowledge sharing in internal crowdsourcing for idea development.

Data on ideas and comments were collected from an idea management system in a Swedish multinational company. The investigation captures the influences of the problem- and solution-related knowledge sharing on ideas based on content analysis and logistic regression analysis.

The results from this study show that sharing knowledge related to solutions in idea development impacts idea acceptance positively, whereas sharing knowledge related to problems in idea development has a negative effect on the likelihood of idea acceptance and these effects of knowledge sharing are moderated by the active author responses.

This research provides managerial implications for firms to deliberately manage knowledge sharing in peer communities in internal crowdsourcing, especially by providing suggestions on problem reframing and solution refining for ideas.

The results contribute to existing theory in terms of extending the view of crowdsourcing in ideation to include how crowds contribute to the development of the problem and the solution during the development of ideas and providing new insights on knowledge sharing in internal crowdsourcing based on problem-solving theory.

This study aims to assess the biodiversity of the study area and estimate the carbon stock of two dry deciduous forest ranges of Banka Forest Division, Bihar, India.

The phytosociological analysis was performed and C stock estimation based on volume determination through nondestructive methods was done.

Phytosociological analysis found total 18,888 [14,893 < 10 cm (diameter at breast height) dbh] and 2,855 (1,783 < 10 cm dbh) individuals at Banka and Bounsi range with basal area of 181,035.00 cm² and 32,743.76 cm², respectively. Importance value index was highest for Shorea robusta in both the ranges. Species diversity index and dominance index, 1.89 and 1.017 at Banka and 1.99 and 5.600 at Bounsi indicated the prevalence of biotic pressure. Decreased dbh and tree height resulted in a lowered growing stock volume as 59,140.40 cm³ ha⁻¹ (Banka) and 71,306.37 cm³ ha⁻¹ (Bounsi). Total C stock at Banka and Bounsi range was 51.8 t ha^-1 and 12.56 t ha⁻¹, respectively where the highest C stock is recorded for Shorea robusta in both the ranges (9.8 t ha⁻¹ and 2.54 t ha^-1, respectively). A positive correlation between volume, total biomass and basal area of tree species with C stock was observed. R² value for Banka range was 0.9269 (volume-C stock), 1 (total biomass-C stock) and 0.647 (basal area-C stock). Strong positive correlation was also established at Bounsi range with R² value of 1. Considering the total forest area enumerated, C sequestration potential was about 194.25 t CO₂ (Banka) and 45.9 t CO₂ (Bounsi). The valuation of C stock was therefore US$2,525.25 (Banka) and US$596.70 (Bounsi).

The research found the potentiality of the study area to sequester carbon. However, for future, the degraded areas would require intervention of management strategies for restoration of degraded lands and protection of planted trees to increase the carbon sequestration potential of the area.

Present study is the first attempt to assess the phytosociology and estimate the regulatory services of forest with respect to biomass and carbon stock estimation for the Banka forest division of Bihar.

The purpose of this study is to examine the effects of nitrogen (N) deposition on clonal growth in a rhizome clonal plant, Leymus chinensis (Trin.) Tzvel.

The study established seven N concentration gradients (0, 2, 4, 8, 16, 32 and 64 g N m⁻²) to simulate the continuous increase in N deposition for the cultivation of L. chinensis seedlings and assess the response mechanism of the cloned L. chinensis plant at different N levels by analyzing the aboveground and belowground plant appearance traits, parent ramets and daughter ramets of resource allocation and biomass allocation.

The results of this study showed that the different N treatment levels could promote clonal growth and had certain regularity under the seven treatments. The addition of N could significantly increase the ramet number, rhizome length, rhizome spacer length, biomass of mother ramets, daughter ramets and belowground L. chinensis population when the N addition was greater than 4 g m⁻²; however, the clonal growth ability of L. chinensis decreased and the rhizome length, ramet number, stem and leaf biomass of daughter ramets and stem biomass of mother ramets significantly decreased when the N addition was greater than 32 g N m⁻².

With global warming, atmospheric N deposition is increasing and it is of great significance to explore the response mechanism of different N levels for the growth of clone plants. This study provides basic data and a theoretical basis for the survival prediction of cloned plants under the background of a global climate change strategy and has important theoretical and practical significance for the scientific management of grasslands in the future.

This paper aims to present a value cocreation framework that furthers understanding of social value cocreation.

This paper is an interdisciplinary conceptual analysis drawing on social enterprise studies, marketing research and philosophical value theory. It applies a visible-hand approach to the study of market relationships and, in line with philosophical research strategies, unfolds its analysis using conceptual distinctions.

This study provides a framework that substantiates the distinction between two modes of value cocreation and identifies the structure of the social enterprise business model. It explains how social enterprises can be conceived as role models for for-profit organizations, and it elucidates why social value cocreation is a demanding objective.

This paper develops an integrative, nondichotomist view of value cocreation that does not conceptualize social and economic value cocreation as opposing goals.

Social enterprises can use the business model structure and two modes of value cocreation and view themselves as role models for for-profit organizations.

This paper applies a visible-hand approach to both for-profit organizations and social enterprises. Using its framework, for-profit organizations can reflect on the consequences of their actions on society and how social value cocreation can improve social enterprise effectiveness.

To the best of the author’s knowledge, this paper is the first to bridge service-oriented approaches to marketing and social enterprise studies using philosophical value theory to improve understanding of social value cocreation.

The paper aims to examine the impact of social capital on the size of the shadow economy in the BIRCS countries over the period 1995–2014.

The authors employ the Bayesian linear regression method to uncover the relationship between social capital and the shadow economy. The method applies a normal distribution for the prior probability distribution while the posterior distribution is determined using the Markov chain Monte Carlo technique.

The results indicate that the unemployment rate and tax burden positively affect the size of the shadow economy. By contrast, corruption control and trade openness are negatively associated with the development of this informal sector. Moreover, the paper's primary finding is that social capital represented by social trust and tax morale can hinder the size of the shadow economy.

This study is limited to the case of the BRICS countries for the period 1995–2014. The determinants of the shadow economy in different groups of countries can be heterogeneous. Moreover, social capital is a multidimensional concept that may consist of various components. This difficulty of measuring the social capital calls for further research on the relationship between other dimensions of social capital and the shadow economy.

Many studies investigate the effect of economic factors on the size of the shadow economy. This paper applies a new approach to discover the issue. Notably, the authors use the Bayesian linear regression method to analyze the relationship between social capital and the shadow economy in the BRICS countries.

Where does one need to intervene in to be most effective? The purpose of this study is to rank areas of the resource system, according to how much of a change can be expected from interventions in an area, in relation to the problem of depleting resources.

Principles of structured analysis are used to model how society uses resources. From this model, nine intervention areas are defined. These intervention areas are ranked in terms of effectiveness, through the use of the analytic hierarchy process.

To be most effective, one must prioritize intervention areas as follows: material inputs to the operation phase; process inputs to the operation phase; products’ longevity; process inputs to the manufacturing phase; and material inputs to the manufacturing phase.

Most decisions are not made on the basis of rigorous analysis but by using heuristics (rules of thumb). The results of this study are expressed as rules of thumb. They can help decision makers prioritize what is most important, but without imposing new ways of working.

In the construction domain, heuristics that generalize the impact of actions (content), instead of intervention areas (context), currently seem to prevail. The heuristics of this study generalize the impact of intervention areas. Therefore, they provide an extra perspective for many decision makers. This extra perspective can help reduce mistakes that are typically made by oversimplifying matters.

This paper aims to spark a debate by presenting the need for developing data ecosystems in Europe that meet the social and public good while committing to democratic and ethical standards; suggesting a taxonomy of data infrastructures and institutions to support this need; using the case study of Barcelona as the flagship city trailblazing a critical policy agenda of smart cities to show the limitations and contradictions of the current state of affairs; and ultimately, proposing a preliminary roadmap for institutional and governance empowerment that could enable effective data ecosystems in Europe.

This paper draws on lessons learned in previous publications available in the sustainability (Calzada, 2018), regions (Calzada and Cowie, 2017; Calzada, 2019), Zenodo (Calzada and Almirall, 2019), RSA Journal (Calzada, 2019) and IJIS (Calzada, 2020) journals and ongoing and updated fieldwork about the Barcelona case study stemming from an intensive fieldwork action research that started in 2017. The methodology used in these publications was based on the mixed-method technique of triangulation via action research encompassing in-depth interviews, direct participation in policy events and desk research. The case study was identified as the most effective methodology.

This paper, drawing from lessons learned from the Barcelona case study, elucidates on the need to establish pan-European data infrastructures and institutions – collectively data ecosystems – to protect citizens’ digital rights in European cities and regions. The paper reveals three main priorities proposing a preliminary roadmap for local and regional governments, namely, advocacy, suggesting the need for city and regional networks; governance, requiring guidance and applied, neutral and non-partisan research in policy; and pan-European agencies, leading and mobilising data infrastructures and institutions at the European level.

From the very beginning, this paper acknowledges its ambition, and thus its limitations and clarifies its attempt to provide just an overview rather than a deep research analysis. This paper presents several research limitations and implications regarding the scope. The paper starts by presenting the need for data ecosystems, then structures this need through two taxonomies, all illustrated through the Barcelona case study and finally, concludes with a roadmap consisting of three priorities. The paper uses previous published and ongoing fieldwork findings in Barcelona as a way to lead, and thus encourage the proliferation of more cases through Cities Coalition for Digital Rights (CCDR).

This paper presents practical implications for local and regional authorities of the CCDR network. As such, the main three priorities of the preliminary roadmap could help those European cities and regions already part of the CCDR network to establish and build operational data ecosystems by establishing a comprehensive pan-European policy from the bottom-up that aligns with the timely policy developments advocated by the European Commission. This paper can inspire policymakers by providing guidelines to better coordinate among a diverse set of cities and regions in Europe.

The leading data governance models worldwide from China and the USA and the advent of Big Data are dramatically reshaping citizens’ relationship with data. Against this backdrop and directly influenced by the General Data Protection Regulation (GDPR), Europe has, perhaps, for the first time, spoken with its own voice by blending data and smart city research and policy formulations. Inquiries and emerging insights into the potential urban experiments on data ecosystems, consisting of data infrastructures and institutions operating in European cities and regions, become increasingly crucial. Thus, the main social implications are for those multi-stakeholder policy schemes already operating in European cities and regions.

In previous research, data ecosystems were not directly related to digital rights amidst the global digital geopolitical context and, more specifically, were not connected to the two taxonomies (on data infrastructures and institutions) that could be directly applied to a case study, like the one presented about Barcelona. Thus, this paper shows novelty and originality by also opening up (based on previous fieldwork action research) a way to take strategic action to establish a pan-European strategy among cities and regions through three specific priorities. This paper can ultimately support practice and lead to new research and policy avenues.