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Despite unanimity in the literature that eco-innovation (EI) leads to sustainable development, evidence remains limited on measuring EI efficiency with the Malmquist productivity index (MPI). In conventional data envelopment analysis (DEA) models, decision-making units (DMUs) are inclined to assign more favorable weights, even zero, to the inputs and outputs to maximize their own efficiency. This paper aims to overcome this shortcoming by developing a common set of weights (CSW).

Using goal programming, this study develops a CSW model to evaluate the EI efficiency of the organization for economic co-operation and development (OECD) countries and track their changes with MPI during 2010–2018.

Achieving a complete ranking of DMUs, findings show the higher discrimination power of the proposed CSW compared with the original DEA models. Furthermore, results reveal that Iceland, Latvia and Luxembourg are the only OECD countries that have incessantly improved their EI productivity (MPI > 1) from 2010 to 2018. On the other hand, Japan is the OECD country that has experienced the highest yearly EI efficiency during 2010–2018. This paper also found that Iceland has the highest MPI over 2010–2018.

More investment in environmental research and development (R&D) projects instead of generic R&D enables OECD members to realize more opportunities for sustainable development through minimizing energy use and environmental pollution in any form of waste and greenhouse gas emissions.

In addition to developing a novel common weights model for DEA-MPI to measure and evaluate the EI of OECD countries, this paper develops a CSW model by including the undesirable outputs for EI analysis.

The purpose of this paper is to discuss the challenges of assessment and management of psychotic symptoms in a background of intellectual disability (ID) and treatment-resistant epilepsy caused by a genetic syndrome.

Ring chromosome 20 [r(20)] syndrome is characterised by the triad of severe refractory epilepsy, mild to severe ID and behavioural problems. This paper describes the presentation of r(20) syndrome in a young woman with moderate ID and treatment-resistant epilepsy, who experiences psychotic symptoms at times of improved seizure control.

There are several diagnostic possibilities for such a presentation, including psychotic symptoms due to adverse effects of anti-epileptic medications and forced normalisation (alternating psychosis).

This paper advocates judicious use of antipsychotic medication to manage psychotic symptoms, as well as involvement of both patient and close family members throughout all stages of care. It is essential to strike a balance between control of epileptic seizures and psychiatric symptoms, providing an optimal benefit to the patients’ quality of life by meeting their complex needs through a multidisciplinary and multi-agency team input.

Universities play a central role in scientific development and progress in societies, so, the need for supporting new businesses in universities becomes very important that science and technology park-based incubators can meet it. The purpose of this paper is to prioritize the factors influencing strategic management of university business incubators (UBIs).

Present research prioritizes the factors influencing strategic management of incubators using analytic network process (ANP). The authors gathered data from UBIs affiliated with science and technology park of Guilan, located in city of Rasht (Iran) using the ANP questionnaire during year 2017.

Factors influencing strategic management of incubators comprised of four main criteria and 14 sub-criteria. The criteria and sub-criteria were ranked based on their importance. Results show that “talented managers” has the highest importance for strategic management of UBIs.

This study offers a novel analysis and contribution to the knowledge of ranking UBIs with a multi-criteria decision-making technique. Results of this research show the relative importance of criteria and sub-criteria, which contributes to further improvement of incubator management. University managers and incubator directors can utilize the findings for better resource allocation and aligning the strategies of incubators with macro strategies of the country.

The purpose of this paper is to investigate the potential or actual role of rural libraries in preserving indigenous knowledge (IK) of the rural residents in South Khorasan province.

The study, based on a qualitative research, was carried out by employing the grounded theory method. Data were collected by semi-structured interviews from the research sample population which included 20 rural males, 10 rural females, 8 librarians and 3 well-informed regional IK specialists. The validity of the research was confirmed by peer evaluation, compounded by detailed thorough explanations and external reviewers’ reaffirmations.

The rural residents of the South Khorasan villages across the province, after having realized the vitality of carrying out this project, were fully motivated and cooperative to provide indigenous knowledge. On the basis of the results from the rural libraries, due to being the solitary knowledge center in the area, these libraries could actively participate in preserving the knowledge and contribute toward the documentation of the indigenous knowledge. This required motivating librarians and increasing their professional, technical, research and verbal skills. The results of the study indicated that, even if the rural libraries of the South Khorasan province did not participate in documentation, preservation, and promotion of the IK and opt for the present form of non-participation, due to their inherent nature, they could become a focal point and play an indispensable role in achieving the objectives by aiding and leading the process at country level and become a focal point for the new generations of rural inhabitants to enlighten themselves and become fully aware of the value of the ancestral knowledge.

Hitherto, none of the researchers in Iran has covered the role of the libraries in general and rural libraries in particular in preserving the indigenous knowledge.

The contemporary landscape of supply chains necessitates a comprehensive integration of multiple components encompassing production, distribution and customer engagement. The pursuit of supply chain harmony underscores the significance of pricing strategies within the framework of dual-channel distribution, particularly when confronted with the dynamics of asymmetric demand performance.

This paper delves into a nuanced decision-making challenge anchored in a dual-channel distribution context featuring a retailer and two distinct products. Notably, the retailer’s decision-making process employs the computational framework of dual grey numbers, a robust tool for handling uncertainty.

This study revolves around applying game theory to manufacturers. Each manufacturer presents its aggregated price proposition to the retailer. Subsequently, the retailer identifies the optimal pricing configuration among the manufacturers' aggregate prices while adhering to constraints such as spatial classification and inventory costs. This article’s contribution extends to delineating the retailer’s capacity to discern the influence of product market potential and the aggregate product cost on the overall demand.

The model’s innovation lies in its harmonious fusion of spatial classification, pricing strategies and inventory control. Notably, this novel integration provides a platform for unraveling the intricate interplay between non-symmetric market potential, production costs and cross-sensitivity. The investigation is underscored by the utilization of the double interval grey numbers, a powerful computational approach that accommodates the inherent uncertainty pervasive in the domain. This study fills a gap in the existing literature by offering an integrated framework unifying spatial allocation, pricing decisions and inventory optimization.

This paper systematically evaluates the existing literature of innovations in freight transport, including all modes, to uncover the key research themes and methodologies employed by researchers to study innovations and their implications in this industry. It analyses the role of transport and the impact of innovations during crises, such as COVID-19.

Qualitative and quantitative analysis of the innovations in freight transport unravels the pre-requisites of such endeavours in achieving a resilient and sustainable transport network that effectively and efficiently operates during a crisis. The authors performed keyword co-occurrence network (KCON) analysis and research focus parallelship network (RFPN) analysis using BibExcel and Gephi to determine the major resulting research streams in freight transport.

The RFPN identified five emerging themes: transport operations, technological innovation, transport economics, transport policy and resilience and disaster management. Optimisation and simulation techniques, and more recently, artificial intelligence and machine learning (ML) approaches, have been used to model and solve freight transport problems. Automation innovations have also penetrated freight and supply chains. Information and communication technology (ICT)-based innovations have also been found to be effective in building resilient supply chains.

Given the growth of e-commerce during COVID-19 and the resulting logistics demand, along with the need for transporting food and medical emergency products, the role of automation, optimisation, monitoring systems and risk management in the transport industry has become more salient. Transport companies need to improve their operational efficiency using innovative technologies and data science for informed decision-making.

This paper advises researchers and practitioners involved in freight transport and innovation about main directions and gaps in the field through an integrated approach for evaluating research undertaken in the area. This paper also highlights the role of crisis, e.g. COVID-19, and its impacts on freight transport. Major contributions of this paper are as follows: (1) a qualitative and quantitative, systematic and effective assessment of the literature on freight transport through a network analysis of keywords supplemented by a review of the text of 148 papers; (2) unravelling major research areas; (3) identifying innovations in freight transport and their classification as technological and non-technological and (4) investigating the impact of crises and disruptions in freight transport.

Conventional data envelopment analysis (DEA) models permit each decision-making unit (DMU) to assess its efficiency score with the most favorable weights. In other words, each DMU selects the best weighting schemes to obtain maximum efficiency for itself. Therefore, using different sets of weights leads to many different efficient DMUs, which makes comparing and ranking them on a similar basis impossible. Another issue is that often more than one DMU is evaluated as efficient because the selection of weights is flexible; therefore, all DMUs cannot be completely differentiated. The purpose of this paper is to development a common weight in dynamic network DEA with a goal programming approach.

In this paper, a goal programming approach has been proposed to generate common weights in dynamic network DEA. To validate the applicability of the proposed model, the data of 30 non-life insurance companies in Iran during 2013-2015 have been used for measuring their efficiency scores and ranking all of the companies.

Findings show that the proposed methodology is an effective and practical approach to measure the efficiency of DMUs with dynamic network structure.

The proposed model delivers more knowledge of the common weight approaches and improves the DEA theory and methodology. This model makes it possible to measure efficiency scores and compare all DMUs from multiple different standpoints. Further, this model allows one to not only calculate the overall efficiency of DMUs throughout the time period but also consider dynamic change of the time period efficiency and dynamic change of the divisional efficiency of DMUs.

Despite the potential of artificial intelligence (AI) systems to increase revenue, reduce costs and enhance performance, their adoption by organisations has fallen short of expectations, leading to unsuccessful implementations. This paper aims to identify and elucidate the factors influencing AI adoption at both the organisational and individual levels. Developing a conceptual model, it contributes to understanding the underlying individual, social, technological, organisational and environmental factors and guides future research in this area.

The authors have conducted a systematic literature review to synthesise the literature on the determinants of AI adoption. In total, 90 papers published in the field of AI adoption in the organisational context were reviewed to identify a set of factors influencing AI adoption.

This study categorised the factors influencing AI system adoption into individual, social, organisational, environmental and technological factors. Firm-level factors were found to impact employee behaviour towards AI systems. Further research is needed to understand the effects of these factors on employee perceptions, emotions and behaviours towards new AI systems. These findings led to the proposal of a theory-based model illustrating the relationships between these factors, challenging the assumption of independence between adoption influencers at both the firm and employee levels.

This study is one of the first to synthesise current knowledge on determinants of AI adoption, serving as a theoretical foundation for further research in this emerging field. The adoption model developed integrates key factors from both the firm and individual levels, offering a holistic view of the interconnectedness of various AI adoption factors. This approach challenges the assumption that factors at the firm and individual levels operate independently. Through this study, information systems researchers and practitioners gain a deeper understanding of AI adoption, enhancing their insight into its potential impacts.

This paper aims to study the features of microstructures and mechanical properties of the joints which were produced by transient liquid phase method. The difference between phases in bonding region identified through metallography pictures and applying hardness and shear strength tests.

The bonding process was carried out at a temperature of 300°C for time durations ranging from 15 to 120 min. The scanning electron microscopy equipped with energy dispersive spectroscopy system and optical microscopy were used to examine microstructural characteristics, and mechanical properties of the joints were studied by applying microhardness and shear tests. The shear tests were conducted by a shear fixture which was mounted on the tensile machine.

The intermetallic compounds of the Cu₆Sn₅ −η and the Cu₃Sn-ε were formed simultaneously in the bonding interface. Although the η-phase, which exhibits scallop-shaped morphology, grows very quickly, upon completion of the isothermal solidification stage, it turns into the ε-phase. The hardness of the bonding interface is significantly higher than that of the substrate. The shear results show that once the bonding process is complete, brittle fracture occurs. Moreover, a greater decrease in strength was observed when the ε-phase is the only phase in the bonding region.

The hardness number of the η-phase is higher than that of the ε-phase. The hardness numbers of the η-phase and the ε-phase are 894 and 689 HV, respectively. The mean shear strength values of the samples that were bonded at 300 °C for 15, 60 and 120 min were 11.7, 9.5 and 5.4 MPa, respectively.

To effectively combat the increasing rates of obesity, it is crucial to explore how environmental factors like sidewalk access impact weight-related outcomes. This study aimed to systematically examine the association between sidewalk accessibility and weight-related outcomes.

Databases were searched by keywords for relevant articles, which were published before March 3, 2024, to report the role of neighborhood sidewalk access on weight-related outcomes. The main findings of the selected articles were extracted from eligible studies by two independent reviewers.

A total of 20 out of 33 studies indicated a significant negative relationship between access to sidewalks and weight-related outcomes. Three studies demonstrated an indirect relationship between access to sidewalks and weight-related outcomes by greater access to physical environments. In addition, five studies reported no clear relationship, and three studies reported a significantly positive relationship between access to sidewalks and weight-related outcomes.

In general, people who live in urban areas with better sidewalk access benefit from better weight-related outcomes. Adults showed this correlation more prominently than adolescents and children. Therefore, sidewalks that have a positive effect on physical activity levels could be considered as a preventive measure against obesity.

One of the weight-related outcomes is obesity. Every community faces numerous challenges due to obesity, which adversely affects the quality of life and health. Environmental factors such as access to sidewalks could be associated with body weight due to lifestyle influences.