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This study offers practical insights into how generative artificial intelligence (AI) can enhance responsible manufacturing within the context of Industry 5.0. It explores how manufacturers can strategically maximize the potential benefits of generative AI through a synergistic approach.

The study developed a strategic roadmap by employing a mixed qualitative-quantitative research method involving case studies, interviews and interpretive structural modeling (ISM). This roadmap visualizes and elucidates the mechanisms through which generative AI can contribute to advancing the sustainability goals of Industry 5.0.

Generative AI has demonstrated the capability to promote various sustainability objectives within Industry 5.0 through ten distinct functions. These multifaceted functions address multiple facets of manufacturing, ranging from providing data-driven production insights to enhancing the resilience of manufacturing operations.

While each identified generative AI function independently contributes to responsible manufacturing under Industry 5.0, leveraging them individually is a viable strategy. However, they synergistically enhance each other when systematically employed in a specific order. Manufacturers are advised to strategically leverage these functions, drawing on their complementarities to maximize their benefits.

This study pioneers by providing early practical insights into how generative AI enhances the sustainability performance of manufacturers within the Industry 5.0 framework. The proposed strategic roadmap suggests prioritization orders, guiding manufacturers in decision-making processes regarding where and for what purpose to integrate generative AI.

Tourism, Technology and Climate Change: The tourism industry is indispensable both for its socio-cultural offerings and its profound economic implications. The economic multiplier effects inherent in the drivers of tourism can stimulate the regional economy even before these areas emerge as tourism meccas. While vast amounts of research have detailed tourism's overarching significance, there is an evident void in understanding its multifaceted impacts, particularly where technological advances, environmental performance (EP) and economic benefits converge. A thorough examination of 907 research records led to this chapter, which identifies these gaps by referencing nine observational and 11 intervention studies. Achieving a Cohen's kappa value of 0.75, the authors note a strong consensus among reviewers, adhering to Cohen's (1940) standards. The findings from the first quarter highlight several areas within the tourism industry that have been under-researched. Particularly, the integration of technology, from ATM infrastructures enhancing tourist financial experiences to digital platforms elevating traveller education and awareness, and tech-driven solutions addressing demographic and ethical considerations in tourism, remains insufficiently explored. Additionally, the authors recognise an existing gap in knowledge regarding the nexus between tourism development and its climatic repercussions, especially before tourism ventures are fully realized. This chapter aims to channel future research into these lesser-trodden areas, fostering a comprehensive grasp of tourism's evolution in the face of rapid technological advancements and its interplay with environmental shifts.

This study aims to evaluate the effectiveness of tax incentives provided by the Ethiopian government in spurring private investment and job creation, using unique administrative and survey data.

The study employs a dataset covering large- and medium-scale manufacturing in Ethiopia from 2012 to 2018, combined with administrative data on actual tax payments and statutory obligations to gauge the impact of tax incentives. Regression analysis using the generalized method of moments (GMM) is used to examine the relationship between tax incentives and employment, taking into account variations in production, distribution and financial costs.

The study finds that tax incentives do not significantly affect employment at conventional significance levels. The incentive elasticity of employment appears to diminish as production, distribution and financial costs increase. Consequently, the incentives provided by the government have not had a substantial impact on employment generation within the manufacturing sector.

This study is unique for its comprehensive analysis of tax incentives in the Ethiopian manufacturing sector using both administrative and survey data. It highlights that increasing production and financial costs can offset the employment benefits of these incentives, emphasizing the need for a more favorable business environment for private investors.

This paper aims to analyze how smart city construction affects destination competitiveness and elucidates the potential mechanisms of digital economy. Also, the regional heterogeneity of smart city construction’s influence on destination competitiveness is discussed.

Given the quasi-natural experiment characteristics of China's smart city construction pilot, this study applies a time-varying difference-in-differences approach using a panel dataset of 272 Chinese prefectural-level cities to examine the causal effects of smart city construction on destination competitiveness.

Results indicate substantial enhancement of urban destination competitiveness from smart city construction, with this effect escalating annually. Digital infrastructure and digital finance serve as influence mechanisms. The positive impacts of smart city construction on urban tourism competitiveness do not differ by geographic location, rather there are significant differences between cities of different administrative levels. The impact of smart city construction on destination competitiveness is more significant in low administrative level cities. The improvement of economic development level and innovation ability helps to exert the positive impact of smart cities on tourism competitiveness.

This study constructs a new panel data set for smart city construction and destination competitiveness based on multi-source data and posits a theoretical linkage among smart city construction, digital economy and destination competitiveness. This paper provides invaluable insights on how to boost destination competitiveness by creating smart cities and leveraging the digital economy. Tourism sectors should proactively engage in smart city construction and foster the digital transformation of tourism.

本文旨在分析智慧城市建设如何影响目的地竞争力, 并阐明数字经济的潜在机制。此外, 还讨论了智慧城市建设对目的地竞争力影响的区域异质性。

鉴于中国智慧城市建设试点的准自然实验特征, 本研究基于272个中国地级城市的面板数据集, 采用双重差分方法检验了智慧城市建设对目的地竞争力的因果影响。

研究结果表明, 智慧城市建设显著增强了城市目的地竞争力, 这种影响每年都在增加。数字基础设施和数字金融是影响机制。智慧城市建设对城市旅游竞争力的积极影响不因地理位置而异, 不同行政级别的城市之间存在显著差异。智慧城市建设对低行政级别城市目的地竞争力的影响更为显著。经济发展水平和创新能力的提高有助于发挥智慧城市对旅游竞争力的积极影响。

本研究基于多源数据构建了一个新的智慧城市建设和目的地竞争力面板数据集, 并在智慧城市建设、数字经济和目的地竞争之间建立了理论联系。本文就如何通过创建智慧城市和利用数字经济来提高目的地竞争力提供了宝贵的见解。旅游部门应积极参与智慧城市建设, 促进旅游业的数字化转型。

El objetivo de este artículo es analizar cómo afecta la construcción de ciudades inteligentes a la competitividad de los destinos y dilucidar los posibles mecanismos de la economía digital. Se aborda también la heterogeneidad regional de la influencia de la construcción de ciudades inteligentes en la competitividad de los destinos.

Dadas las características de experimento casi natural del proyecto piloto de construcción de ciudades inteligentes en China, este estudio aplica un enfoque de diferencias en diferencias temporales utilizando un conjunto de datos de panel de 272 ciudades chinas de nivel de prefectura para examinar los efectos causales de la construcción de ciudades inteligentes sobre la competitividad de los destinos.

Los resultados indican una mejora sustancial de la competitividad de los destinos urbanos gracias a la construcción de ciudades inteligentes, efecto que aumenta cada año. La infraestructura digital y las finanzas digitales actúan como mecanismos de influencia. Los efectos positivos de la construcción de ciudades inteligentes sobre la competitividad Del turismo urbano no difieren en función de la ubicación geográfica, sino que las diferencias significativas se producen entre ciudades de diferentes niveles administrativos. El impacto de la construcción de ciudades inteligentes en la competitividad de los destinos es más significativo en las ciudades de bajo nivel administrativo. La mejora del nivel de desarrollo económico y la capacidad de innovación contribuyen al impacto positivo de las ciudades inteligentes en la competitividad turística.

Este estudio construye un nuevo conjunto de datos de panel para la construcción de ciudades inteligentes y la competitividad de los destinos basado en datos de múltiples fuentes y plantea un vínculo teórico entre la construcción de ciudades inteligentes, la economía digital y la competitividad de los destinos. Este artículo ofrece un valioso conocimiento sobre cómo impulsar la competitividad de los destinos mediante la creación de ciudades inteligentes y el aprovechamiento de la economía digital. Los sectores turísticos deberían participar de forma proactiva en la construcción de ciudades inteligentes y fomentar la transformación digital del turismo.

Empirical literature is the primary source of understanding how policing can effectively reduce criminal activities. Spatial analyses can identify particular effects that can explain and assist in constructing appropriate regional strategies and policies; nevertheless, studies that use spatial regression methods are more limited and can provide a perspective on specific effects in a more disaggregated regional context.

This research aims to conduct a systematic literature review (SLR) to understand the relationship between crime indicators and police production using spatial regression models. We consider a combination of Kitchenham and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocols as a methodological strategy in five bibliographic databases for collecting scientific articles.

The SLR suggests a limited amount of evidence that meets the criteria defined in the research strategy. Several particularities are observed regarding police and criminal production metrics, either in terms of aggregation level, indicator transformations or scope of analysis. A broader time perspective did not necessarily indicate statistical significance compared to models with a single-period sample.

The findings suggest the possibility of expanding efforts by the public sector to provide policing data with the intention of conducting appropriate research using spatial analysis. This step could allow for a more robust integration between the public sector and researchers, strengthening policing strategies, evaluating the effectiveness of public security policies and assisting in the development of strategies for future policy actions.

Limited empirical evidence meets the criteria of spatial regression models with temporal components considering police production and criminality indicators. Constructing an SLR with this scope is an unprecedented contribution to the literature. The discussion can enhance the understanding of approaches for studying the relationship between police efforts and crime prevention.

This paper aims to explore three operations and supply chain management (OSCM) approaches for meeting the 2 °C targets to counteract climate change: adaptation (adjusting to climatic impacts); mitigation (innovating towards low-carbon practices); and carbon-removing negative emissions technologies (NETs). We suggest that adaptation nor mitigation may be enough to meet the current climate targets, thus calling for NETs, resulting in the following question: How can operations and supply chains be reconceptualized for NETs?

We draw on the sustainable supply chain and transitions discourses along with interview data involving 125 experts gathered from a broad research project focused on geoengineering and NETs. We analyze three case studies of emerging NETs (biochar, direct air carbon capture and storage and ocean alkalinity enhancement), leading to propositions on the link between OSCM and NETs.

Although some NETs are promising, there remains considerable variance and uncertainty over supply chain configurations, efficacy, social acceptability and potential risks of unintended detrimental consequences. We introduce the concept of transformative OSCM, which encompasses policy interventions to foster the emergence of new technologies in industry sectors driven by social mandates but lack clear commercial incentives.

To the best of the authors’ knowledge, this paper is among the first that studies NETs from an OSCM perspective. It suggests a pathway toward new industry structures and policy support to effectively tackle climate change through carbon removal.

This article explores the heterogenous social mechanisms that drive responsible environmental behaviours by investigating differences in the mean effect of the psychosocial determinants of the intention to buy organic foods.

Using data for a representative sample of the Spanish population, we estimated the mean effect of the constructs represented in the responsible environmental behaviour (REB) theory that affect sustainable food consumption, and examined the social mechanisms that may explain heterogeneity in the mean effect of those constructs. Confirmatory factor analysis, linear regression, and latent class regression were used in the analysis.

We found that the effect of REB’s psychosocial constructs varied significantly, demonstrating social heterogeneity in the estimated average effect. We identified different social mechanisms that explain variations in organic food purchase intentions: environmental attitudes and social norms shape these intentions among socioeconomically privileged consumers, whereas personal norms shape these intentions among less socially advantaged consumers.

Our research contributes to the literature by highlighting the existence of differing social mechanisms explaining organic food purchase intentions. The uncovering of three social mechanisms explaining differences in the mean effect of factors driving those intentions provides valuable insights with regard to both further developing a holistic framework for responsible environmental behaviours and developing new public policies and marketing strategies aimed at improving sustainable food consumption.

This study analyzes the performance implications of adopting blockchain to support supply chain business processes. The technology holds as many promises as implementation challenges, so interest in its impact on operational performance has grown steadily over the last few years.

Drawing on transaction cost economics and the contingency theory, we built a set of hypotheses. These were tested through a long-term event study and an ordinary least squares regression involving 130 adopters listed in North America.

Compared with the control sample, adopters displayed significant abnormal performance in terms of labor productivity, operating cycle and profitability, whereas sales appeared unaffected. Firms in regulated settings and closer to the end customer showed more positive effects. Neither industry-level competition nor the early involvement of a project partner emerged as relevant contextual factors.

This research presents the first extensive analysis of operational performance based on objective measures. In contrast to previous studies and theoretical predictions, the results indicate that blockchain adoption is not associated with sales improvement. This can be explained considering that secure data storage and sharing do not guarantee the factual credibility of recorded data, which needs to be proved to customers in alternative ways. Conversely, improvements in other operational performance dimensions confirm that blockchain can support inter-organizational transactions more efficiently. The results are relevant in times when, following hype, there are signs of disengagement with the technology.

The study aims to identify the practical borders of AI legal personality and accountability in human-centric services.

Using a framework tailored for AI studies, this research analyses structured interview data collected from auditors based in Poland.

The study identified new constructs to complement the taxonomy of arguments for AI legal personality: cognitive strain, consciousness, cyborg paradox, reasoning replicability, relativism, AI misuse, excessive human effort and substitution.

The insights presented herein are primarily derived from the perspectives of Polish auditors. There is a need for further exploration into the viewpoints of other key stakeholders, such as lawyers, judges and policymakers, across various global contexts.

The findings of this study hold significant potential to guide the formulation of regulatory frameworks tailored to AI applications in human-centric services. The proposed sui generis AI personality institution offers a dynamic and adaptable alternative to conventional legal personality models.

The outcomes of this research contribute to the ongoing public discourse on AI’s societal impact. It encourages a balanced assessment of the potential advantages and challenges associated with granting legal personality to AI systems.

This paper advocates for establishing a sui generis AI personality institution alongside a joint accountability model. This dual framework addresses the current uncertainties surrounding human, general AI and super AI characteristics and facilitates the joint accountability of responsible AI entities and their ultimate beneficiaries.

Calculating an organization's carbon footprint is crucial for assessing and implementing emission reductions. Although Finnish higher education institutions (HEIs) aim for carbon neutrality by 2030, limited research exists on plans to reach a similar target in any country. This paper aims to address the shared and individual challenges Finnish HEIs have with carbon footprint calculations, reductions, resources and offsetting.

A survey was targeted to sustainability experts in all 38 HEIs in Finland to identify key patterns and trends in the focus fields of the study. SWOT analysis was used to classify main strengths, opportunities, weaknesses and threats, based on which a series of policy recommendations was drafted.

Finnish HEIs are committed to carbon footprint tracking (97%, annually by 87%). The lack of standardization and the number of external stakeholders complicate accounting indirect emissions, impeding comparability and reliability. Only 39% had set separate emission reduction targets, suggesting a preference for carbon footprint over other environmental impact indicators. Insufficient monetary and human resources emerged in 23% of institutions, especially those smaller in size. Only 52% had clear offsetting plans, with shared concerns over trust and responsibility.

By including both research universities and universities of applied sciences, the findings provide an unprecedented outlook into the entire Finnish HEI sector. The policy recommendations guide HEIs both locally and globally on how to improve their transparency and scientific integrity, reflect on core successes and weaknesses and how they complete their objectives of education, research and social impact while promoting stronger sustainability.