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The objective of this paper is to propose a methodology to estimate the benefits and costs of stakeholder engagement (SE). Indeed, in the transport sector, it is consolidated that a good decision-making process foresees the involvement of the main stakeholders, but what are the benefits and costs of the SE? How to quantify these impacts and explicitly take them into account in a cost-benefit analysis? In this paper, an attempt to answer these questions is provided.

In this paper, a methodology is proposed to estimate the benefits and costs of SE. Moreover, the proposed methodology is applied to a case study with an attempt to identify direct and indirect cost and benefit drivers within the context.

A range of examples of the monetary costs and benefits of SE is provided through the case study of the high-speed rail corridor connecting Bari and Naples in Italy.

Limits in quantifying all the aspects of engagement.

To be adopted by public administrations when deciding whether carrying out a project.

Social inclusion is a must in any decision-making process concerning big projects affecting the community.

The original value of this paper is to provide a contribution to the current literature on the quantitative representation of the impacts of SE. Indeed, a methodology to quantify and monetize the costs and benefits of SE is proposed.

Intrapreneurial ability (IA) of employees strengthens an organization's internal as well as external growth. Employees' IA makes innovation a continuous practice and augments organization's intellectual capital (IC). This intellectual capital-based intrapreneurial ability (ICIA) helps professionals to effectively handle changes in the business ecosystem by creating innovative solutions. The onus of assessing and inculcating ICIA is a joint responsibility of both academia and industry. In academia, teacher as a servant leader (TASL) contributes towards building ICIA of working professionals (WP) by enhancing their self-efficacy (SE). The paper aims to strengthen the industry–academia interface by analyzing the role of TASL and SE in influencing the ICIA of WP.

Using a stratified sampling technique, data from 387 WP is analyzed on SmartPLS-4 to study the interrelationship between the stated constructs and the role of SE as a mediator between TASL and ICIA. PLSpredict is used to study the predictive relevance of the proposed model.

High R² = 0.654 shows that 65% of ICIA is determined by SE and TASL; reflecting model's robustness. SE partially mediates the relationship between TASL and ICIA. Results reported a higher ICIA of male WP than their female counterpart. The results indicate the low predictive accuracy of the model.

The proposed model of industry–academia partnership allows assessment of ICIA for enhancing corporate value in the present gig economy. The study also highlights the relevance of ICIA, particularly, for developing economies. In knowledge-driven economy, exploring the new ICIA will help organizations to draft a more robust performance measurement system.

This unique industry–academia partnership studies the role of TASL towards enhancing SE and ICIA of WP. The novelty of ICIA would enrich and provide a new perspective in IA literature. Additionally, the study also examines the role of gender in the ICIA of WP.

This study aims to examine the technical efficiency of the chemical-free farming system in India using a hybrid combination of data envelopment analysis (DEA) and machine learning (ML) approaches.

The study used a two-stage approach. In the first stage, the efficiency scores of decision-making units’ efficiency (DMUs) are obtained using an input-oriented DEA model under the assumption of a variable return to scale. Based on these scores, the DMUs are classified into efficient and inefficient categories. The 2nd stage of analysis involves the identification of the most important predictors of efficiency using a random forest model and a generalized logistic regression model.

The results show that by using their resources efficiently, growers can reduce their inputs by 34 percent without affecting the output. Orchard's size, the proportion of land, grower's age, orchard's age and family labor are the most important determinants of efficiency. Besides, growers' main occupation and footfall of intermediaries at the farm gate also demonstrate significant influence on efficiency.

The study used only one output and a limited set of input variables. Incorporating additional variables or dimensions like fertility of the land, climatic conditions, altitude of the land, output quality (size/taste/appearance) and per acre profitability could yield more robust results. Although pineapple is cultivated in all eight northeastern states, the data for the study has been collected from only two states. The production and marketing practices followed by the growers in the remaining six northeastern states and other parts of the country might be different. As the growers do not maintain farm records, their data might suffer from selective retrieval bias.

Given the rising demand for organic food, improving the efficiency of chemical-free growers will be a win-win situation for both growers and consumers. The results will aid policymakers in bringing necessary interventions to make chemical-free farming more remunerative for the growers. The business managers can act as a bridge to connect these remote growers with the market by sharing customer feedback and global best practices.

Although many developments have happened to the DEA technique, the present study used a traditional form of DEA. Therefore, future research should combine ML techniques with more advanced versions like bootstrap and fuzzy DEA. Upcoming research should include more input and output variables to predict the efficiency of the chemical-free farming system. For instance, environmental variables, like climatic conditions, degree of competition, government support and consumers' attitude towards chemical-free food, can be examined along with farm and grower-specific variables. Future studies should also incorporate chemical-free growers from a wider geographic area. Lastly, future studies can also undertake a longitudinal estimation of efficiency and its determinants for the chemical-free farming system.

No prior study has used a hybrid framework to examine the performance of a chemical-free farming system.

We take Cumulative Prospect Theory (CPT) seriously by rigorously estimating structural models using the full set of CPT parameters. Much of the literature only estimates a subset of CPT parameters, or more simply assumes CPT parameter values from prior studies. Our data are from laboratory experiments with undergraduate students and MBA students facing substantial real incentives and losses. We also estimate structural models from Expected Utility Theory (EUT), Dual Theory (DT), Rank-Dependent Utility (RDU), and Disappointment Aversion (DA) for comparison. Our major finding is that a majority of individuals in our sample locally asset integrate. That is, they see a loss frame for what it is, a frame, and behave as if they evaluate the net payment rather than the gross loss when one is presented to them. This finding is devastating to the direct application of CPT to these data for those subjects. Support for CPT is greater when losses are covered out of an earned endowment rather than house money, but RDU is still the best single characterization of individual and pooled choices. Defenders of the CPT model claim, correctly, that the CPT model exists “because the data says it should.” In other words, the CPT model was borne from a wide range of stylized facts culled from parts of the cognitive psychology literature. If one is to take the CPT model seriously and rigorously then it needs to do a much better job of explaining the data than we see here.

Brazil’s regional inequality is an important topic due to the large and persistent differences in development between states and the high levels of inequality in the country. These variations in development can potentially render survey data inaccurate since the significance of capital income varies across the states. Besides, previous studies incorporating tax and national accounts data globally have mainly focused on measuring the income distribution at the country-level. This approach can limit the understanding of inequality, especially when considering large countries such as Brazil.

The methodology used to construct these estimates follows the guidelines of the Distributional National Accounts, whose core goal is to provide income distribution measures consistent with macroeconomic aggregates and harmonized across countries and time. The procedure has three main steps: first, it corrects the survey’s underrepresentation of top incomes using tax data. Then, it accounts for national income items not included in the survey or tax data, such as imputed rents and undistributed profits. Finally, it ensures that all components match the national income.

Compared to survey-based estimations, the results reveal a new angle on the state-level inequality. This study indicates that Amazonas, Rio de Janeiro and São Paulo have a more concentrated income distribution. The top 1\% of earners in these states receives around 28\% of total pre-tax income, while the top 10\% receive nearly 60\%. On the other end, Amapá (AP), Acre (AC), Rondônia (RO) and Santa Catarina (SC) are the states where the income distribution is less concentrated. There were no significant changes in the income distribution across the states during the period analyzed.

This study combines survey, tax and national accounts data to construct new estimates of Brazil’s state-level income distribution from 2006 to 2019. Previous results only considered income captured in surveys, which usually misses a significant part of capital incomes. This limitation may bias comparisons as capital income has different importance across the states. The new estimates represent the income of top groups more accurately, account for the entire national income and enable to compare regional inequality levels consistently with other countries.

Throughout the 21st century, US households have experienced unprecedented levels of leverage. This dynamic has been exacerbated by income shortfalls during the COVID-19 crisis. Leveraging and deleveraging decisions affect household consumption. This study investigates the effect of the dynamics of household leverage and consumption on the stock market.

The authors explore the relation between household leverage and consumption in the context of the consumption capital asset pricing model (CCAPM). The authors test the model's implication that leverage has a negative risk premium by transforming the asset pricing restriction into an unconditional linear factor model and estimate the model using the general method of moments procedure. The authors run time-series regressions to estimate individual stocks' exposures to leverage, and cross-sectional regressions to investigate the leverage risk premium.

The authors show that shocks to household debt have strong and lasting effects on consumption growth. The authors extend the CCAPM to accommodate this effect and find, using various test assets, a negative risk premium associated with household deleveraging. Looking at individual stocks the authors show that the deleveraging risk premium is not explained by well-known risk factors.

This paper contributes to the literature on the role of leverage in economics and finance by establishing a relation between household leverage and spending decisions. The authors provide novel evidence that households' leveraging and deleveraging decisions can be a fundamental and influential force in determining asset prices. Further, this paper argues that household leverage might explain the small, persistent, and predictable component in consumption growth hypothesised in the long-run risk asset pricing literature.

The impacts of institutional quality on entrepreneurship are well established. However, the effects of an external factor, such as the shadow economy, that moderates this relationship have largely been neglected in existing literature. As such, this paper investigates how the shadow economy moderates the effects of institutional quality on entrepreneurship in a global sample of 79 economies from 2006 to 2018, when the latest required data are available.

This paper utilizes the fixed-effect and generalized method of moments (GMM) estimation techniques. Various scenarios have been considered for the robustness of the analysis, including different estimation techniques, different estimates of the shadow economy and various subsamples of countries with different income levels.

Empirical findings indicate that improved institutional quality boosts entrepreneurship activities, while the extended shadow economy is associated with reduced entrepreneurship activities. Interestingly, the positive impacts of institutional quality on entrepreneurship will be lessened with a larger shadow economy. These findings have remained largely unchanged across samples of countries and different proxies and estimation techniques.

Findings from this paper offer policymakers the relationships between institutional quality, shadow economy and entrepreneurship and the moderating effects of shadow economy on the institutional quality–entrepreneurship nexus. The implication is that institutional quality should be strengthened while the shadow economy should be controlled to promote entrepreneurship initiatives.

To the best of the author's knowledge, this is the first empirical study to explore the moderating effects of the shadow economy on the institutional quality–entrepreneurship nexus.

This study motivated by humanistic care aims to identify hospitality frontline employees’ alienation in Taiwan during the COVID-19 pandemic, and based on the job demands-resources (JD-R) model, the mediating role of alienation between job characteristics and organizational citizenship behavior (OCB) is discussed.

The authors drew on the JD-R model to delineate the mechanisms by which job demands (including emotional dissonance and work–home conflict) and job resources (including job support, training and possibility for career development) affect OCB through employees’ alienation. This study adopted snowball sampling and purposive sampling to conduct a questionnaire survey aimed at Taiwanese hospitality frontline employees. A total of 373 valid questionnaires were retained, and structural equation model was used to test the research hypotheses.

The results revealed that job demands of emotional dissonance and work–family conflict positively affect alienation; job resources of job support, training and possibility for career development negatively affect alienation; alienation negatively affects OCB; and alienation mediates the relationship between job characteristics and OCB fully.

Considering that alienation plays a full mediating role between job characteristics and organizational outcomes, this study put forward specific suggestions on how to increase job resources and reduce job demands to weaken alienation and further improve organizational performance in management practices. And practical implications were provided to help hospitality human resource management deal with the issue of talents retention. In addition, “work authenticity” should be introduced as a mediator in the future research. “Work authenticity” reflects employees’ positive working life state and is the opposite of “alienation.” The effectiveness of employees’ positive and negative working life state in communicating job characteristics and organizational outcomes can be compared.

The specific alienation experience of hospitality frontline employees is defined. Moreover, by introducing the alienation theory, this study demonstrates the health impairment path of JD-R model and suggests that job characteristics affect OCB through the full mediation of alienation.

本研究以人文关怀为动机, 明确了COVID-19疫情期间台湾酒店一线员工的异化状态, 并基于工作需求-资源理论模型, 探讨了异化在工作特性与组织公民行为之间发挥的中介作用。

笔者运用工作需求-资源模型以阐释工作需求（包括情绪失调和工作-家庭冲突）和工作资源（包括工作支持、培训和职业发展潜能）透过员工的异化影响组织公民行为的机制。本研究采用滚雪球抽样和目的性抽样的抽样方式, 对台湾酒店一线员工开展问卷调查; 留存有效问卷373份, 并采用结构方程模型对研究假设进行检验。

本研究揭示了情绪失调和工作-家庭冲突的工作需求正向影响异化; 工作支持、培训和职业发展潜能的工作资源对异化产生负面影响; 异化对组织公民行为产生负面影响; 异化在工作特性与组织公民行为的关系中起完全中介作用。

综合异化在工作特性与组织成果之间起着完全的中介作用, 本研究就管理实践中如何增加工作资源和减少工作需求以减弱异化并进一步提高组织绩效提出了具体建议, 以此帮助酒店人力资源管理部门处理留住人才的问题。此外, 应引入反映员工积极工作状态的“工作真实性”（即“异化”的对立面）作为中介, 比较员工积极和消极工作状态在沟通工作特性和组织成果上的有效性。

本研究明确了酒店一线员工具体的异化体验。此外, 透过引入异化理论, 本研究实证了工作需求-资源模型的健康损害路径, 并揭示了工作特性通过异化的完全中介作用影响组织公民行为。

Este estudio motivado por la atención humanística identificó la alienación de los empleados de primera línea de la hostelería en Taiwán durante la pandemia de COVID-19 y, basándose en el modelo de exigencias laborales-recursos (JD-R), se analizó el papel mediador de la alienación entre las características laborales y el comportamiento de ciudadanía organizacional fue discutido.

Nos basamos en el modelo JD-R para delinear los mecanismos por los que las exigencias del puesto de trabajo (incluida la disonancia emocional y el conflicto entre el trabajo y el hogar) y los recursos del puesto de trabajo (incluido el apoyo laboral, la formación y la posibilidad de desarrollo profesional) afectan a la organización. Del comportamiento ciudadano (OCB) a través de la alienación de los empleados. Este estudio adoptó el muestreo de bola de nieve y el muestreo intencional para realizar una encuesta por cuestionario dirigida a los empleados de primera línea de la hostelería taiwanesa. Se obtuvieron 373 cuestionarios válidos y se utilizó un modelo de ecuaciones estructurales para probar las hipótesis de la investigación.

Los resultados revelaron que las demandas laborales de disonancia emocional y conflicto trabajo-familia afectan positivamente a la alienación; los recursos laborales de apoyo al trabajo, formación y posibilidad de desarrollo profesional afectan negativamente a la alienación; la alienación afecta negativamente al comportamiento de ciudadanía organizacional; la alienación media totalmente la relación entre las características laborales y el comportamiento de ciudadanía organizacional.

Teniendo en cuenta que la alienación desempeña un papel mediador total entre las características del puesto de trabajo y los resultados organizativos, este estudio presentó sugerencias específicas sobre cómo aumentar los recursos del puesto de trabajo y reducir las exigencias del mismo para debilitar la alienación y mejorar aún más el desempeño organizacional en las prácticas de gestión. Y se aportaron implicaciones prácticas para ayudar a abordar la cuestión de retención de talentos en la gestión de los recursos humanos en la hostelería. Además, la “autenticidad del trabajo” debería introducirse como mediador en la investigación futura. La “autenticidad laboral” refleja el estado de vida laboral positivo de los empleados y es lo contrario de la “alienación”. Se puede comparar la eficacia del estado de vida laboral positivo y negativo de los empleados en la comunicación de las características del trabajo y los resultados organizacionales.

Se define la experiencia específica de alienación de los empleados de primera línea de la hostelería. Además, mediante la introducción de la teoría de la alienación, este estudio demuestra la trayectoria de deterioro de la salud del modelo JD-R, y sugiere que las características del puesto de trabajo afectan al comportamiento de ciudadanía organizacional a través de la mediación total de la alienación.

We evaluate the hypothesis of temporal stability in risk preferences using two recent data sets from longitudinal lab experiments. Both experiments included a combination of decision tasks that allows one to identify a full set of structural parameters characterizing risk preferences under Cumulative Prospect Theory (CPT), including loss aversion. We consider temporal stability in those structural parameters at both population and individual levels. The population-level stability pertains to whether the distribution of risk preferences across individuals in the subject population remains stable over time. The individual-level stability pertains to within-individual correlation in risk preferences over time. We embed the CPT structure in a random coefficient model that allows us to evaluate temporal stability at both levels in a coherent manner, without having to switch between different sets of models to draw inferences at a specific level.

The integration of digital technologies into education has brought about a profound transformation, fundamentally reshaping the learning landscape. The purpose of this study is to underscore the importance of investigating the factors influencing students’ engagement (SE) in this evolving digital era, particularly within formal digital learning environments. To address this need, the study is grounded in self-determination theory (SDT) and presents a comprehensive model comprising interconnected elements: digital competence (DC), smartphone use (SPU), perceived autonomy (PA), digital formal learning (DFL) and SE.

The research conducted an investigation within Saudi Arabian universities, collecting a robust data set of 392 cases. This data set underwent rigorous analysis to validate the proposed model. To untangle the intricate relationships within the framework, the study used partial least squares structural equation modelling. Given the distinct dimensions of the two constructs under study, the researcher used a disjoint two-stage approach to establish reflective-formative higher-order constructs (HOC).

The findings revealed that digital literacy and digital skills (DS) constitute the foundational constituents of DC. Simultaneously, the study identified facilitation, distraction and connectedness as integral components of SPU. Importantly, the study established that DC, SPU, PA and DFL significantly influence SE. Furthermore, the research illuminated the mediating roles played by SPU, PA and DFL in the complex relationship between DC and SE.

This study advances the literature by delineating the dynamic interplay between DC, SPU and SE in digital learning. It extends SDT within educational contexts, emphasizing the role of internal motivations and DS. Methodologically, it innovates through reflective-formative HOCs, deepening the analysis of complex educational constructs. Managerially, it guides institutions in enhancing DC and integrating smartphones effectively into learning, advocating for tailored strategies to foster engaging and autonomous digital learning environments, thereby enriching both theoretical understanding and practical application in education.