Integrated Model Research Articles

Navigating employment and overeducation: comparative study of immigrant experiences in 17 Western European nations

ABSTRACT The labor market integration of migrants, focusing on employment and job quality, differs notably across Southern and Continental-Northern European nations, often involving trade-offs. Nonetheless, little is known about whether these diverse migrant inclusion models in European labor markets extend to the combination of employment and overeducation. Additionally, the role of gender in this context remains unclear. While overeducation is more prevalent among immigrants compared to native, its prevalence varies across countries. To fill this gap, we analyzed data from the 2015–2019 European Labor Force Survey in 17 European countries, considering gender and migrant origin – Western vs. non-Western. Results show that non-Western migrants and migrant women face more challenges than Western migrants and male counterparts, respectively. Among males, a trade-off model predominates, with low employment penalties but high overeducation penalties in Mediterranean countries, and vice versa in Continental and some Nordic nations. For females, those in Southern Europe align with the Mediterranean trade-off model, while those in most Continental and Nordic countries experience a double penalty. In Liberal countries, male migrants tend toward the Mediterranean trade-off model, while female migrants align with the integration model.

Investing in the future: an integrated model for analysing user attitudes towards Robo-advisory services with AI integration

Purpose Recognizing the importance of Robo-advisors in digital financial services, this paper aims to analyse the users’ perception and acceptability of artificial intelligence (AI) in digital investment solutions using an extended “Technology Acceptance Model” (TAM). Design/methodology/approach The model is tested using 454 online valid responses received from Indian Fintech users via direct path analysis, mediation and moderation. Findings The study’s findings show that trust, perceived usefulness and perceived risk all significantly impact users’ attitudes towards Robo-advisors. In contrast, ease of use and social influence did not impact users’ attitudes statistically. Furthermore, the results indicate that their attitudes and ease of use influence users’ intentions to adopt Robo-advisors. Moreover, the moderation effect of gender partly supports the overall model. Specifically, in the path between attitudes and their antecedents, gender plays a role in influencing the relationships among these variables. This aligns with preliminary research in the field, providing additional insight into how gender may moderate the factors influencing users’ attitudes and intentions regarding Robo-advisory services. Research limitations/implications This research study also reveals that trust, perceived risk, ease of use and demographic factors influence the adoption of Robo-advisory services. It is functional, but its sample selection is not probabilistic and overly emphasizes gender. Future research should use probabilistic sampling, other demographic factors and experience and situational factors. Also, it is necessary to examine how convenient and satisfying it is to communicate with service providers. Filling these gaps will improve the knowledge of consumer behaviour in the context of Fintech adoption and develop the current research. Practical implications This study posits that perceived usefulness, trust, perceived risk and ease of use remain core determinants of adopting Robo-advisory services. So, to improve the level of trust of users, it is necessary to develop security measures, data clarity and quality and customer support. Enhancing ease of use by incorporating better interface gestures is always beneficial for increasing the number of users and their level of satisfaction. As identified in previous studies, practical solutions will be achieved by pursuing the increased use of technology while leveraging AI for personal services and minimizing perceived risks, which will strengthen more advanced security measures as well as sufficiently clear communication. Originality/value The paper aims to extend the TAM by incorporating measures of trust and social influence to identify the factors that drive the adoption of Robo-advisors. In doing so, the paper may contribute to developing a more comprehensive understanding of the factors that shape consumers’ attitudes and intentions towards these technologies. Moreover, the paper appears to examine the moderating effect of gender on attitude and its predictors, which could provide insights into how gender characteristics may impact the adoption of Robo-advisors.

Clinical and Cognitive Metacognition in Gaming and Gambling Disorder: A Narrative Review

Abstract Purpose of this review To review and reconcile the methodologies and understandings of metacognition from both cognitive science and psychopathology in Gaming Disorder and Gambling Disorder to enhance interdisciplinary communication and methodological exchange. Recent findings While clinical metacognition research in gaming and gambling disorders is established, exploration into specific metacognitive mechanisms within these domains is still nascent. Summary This review delineates various forms of metacognition and clinical measurements of metacognition in Gaming Disorder and Gambling Disorder. The discussion presents a new integrated model of metacognition in behavioural addictions that generates a research agenda to understand and target these addictions with more effective interventions.

Impact of the Financial Advisor on Clients’ Financial Outcomes: An Integrative Model

A financial advisor may either act as a consultant or may be delegated the entire financial advising process. In both cases, researchers tend to conclude that advisorshavean impact on their clients’financial outcomes. However, there is no agreementon the nature and extent of this impact. We argue that such discordance in the results being reported in prior research arises from the different theoretical lens used to observe the phenomenon: agency theory, trust theory, and the concept of knowledge. In our view, the complexity of advisors’ contribution to their clients’ outcomes requires a novel approach that extends beyond a single theory. Relying upon aliterature review, we propose an integrative multi-theory model that reconciles prior findings and illustrates how financial advisers impact clients’ outcomes at each step within the financial advising process. Practice-grounded, the model also provides a causal mechanism clarifying the opaque and complex services provided by the financial advisor.

Understanding behavioral intentions in urban travel reservation: a combined model of rational motivation and social norms

ABSTRACT The travel reservation strategy (TRS) is more flexible and refined than traditional traffic demand management methods. There is limited research discussing the implementation of travel reservations during peak hours for congested bottleneck roads in urban areas. Furthermore, previous studies have not explored the behavioral intentions of urban residents regarding travel reservations. This study explored the essential psychological characteristics affecting travelers’ acceptance of TRS and the potential causal relationships between these variables. We proposed the Tech-Norm-Behavior Integration model that integrates the Theory of Planned Behavior, Technology Acceptance Model, and Norm Activation Model to examine travelers’ intentions to use travel reservations driven by rational and normative motivations. We used the structural equation model to verify the integrated model's validity. The results demonstrate that personal norms significantly impact behavioral intentions, followed by attitude and perceived behavioral control. It confirms that TRS is a prosocial traffic demand management strategy have significant mediating effects.

Performance evaluation of industry-education integration in higher education from the perspective of coupling coordination-an empirical study based on Chongqing.

The coupling coordination between higher education and regional industries is an effective way to enhance the performance of industry-education integration and an important driving force for promoting sustainable economic and social development. This article aims to evaluate the performance level of industry-education integration in higher education from the perspective of coupling coordination between industry and education, and to analyze its sustainable development trends. To achieve this, a framework for the industry-education complex system is constructed based on the theory of coupling coordination, and a performance evaluation model for industry-education integration is established. The "structure-conduct-performance" (S-C-P) analysis paradigm of industrial organization theory is used to design a performance evaluation indicator system, and the entropy weight method is applied to assign weights to the indicator system. Empirical research is conducted on Chongqing based on statistical data from 2000 to 2022. The results show that: (1) During the sample period, the construction effectiveness of industry-education integration in higher education in Chongqing is relatively significant, and the coordination level between regional industries and higher education continues to rise. (2) The orderly development level of the two subsystems of regional industries and higher education alternately rises, jointly promoting the continuous improvement of the performance level of industry-education integration, which is the main driving factor for performance improvement. (3) The stagnation of the coupling strength between regional industries and higher education is a key obstacle to further improving the performance of industry-education integration. Industry-education integration is a systematic project that should be promoted collaboratively from the perspectives of the regional industrial subsystem, higher education subsystem, industry-education complex system, and external environment to continuously enhance the performance level.

Factors Shaping the Adoption of AI Tools among Gen Z: An Extended UTAUT2 Model Investigation Using CB-SEM

Artificial Intelligence, at the forefront of innovation and intelligence, is redefining the pace of life and work, notably within education. This study investigates the determinants influencing Gen Z's behavioral intentions (BI) to integrate AI-powered tools within Indian Higher Educational Institutions (HEIs) by extending the UTAUT2 model with four additional constructs: trustworthiness, personal innovativeness, perceived task excellence, and perceived privacy concern. The data gathered from 430 respondents within Indian HEIs through an online survey following purposive sampling was meticulously analyzed using the structural equation modeling approach in AMOS. The findings validate the applicability of the UTAUT2 model for understanding AI tool integration in the Indian context, with an explanatory power of 34.2%. The study highlights the beneficial impact of hedonic motivation, perceived task excellence, facilitating conditions, and performance expectancy on Gen Z's intention to integrate AI tools. Additionally, the study suggests recommendations for future research and outlines implications based on these findings.

Mesoscale explorer: Visual exploration of large-scale molecular models.

The advent of cryo-electron microscopy (cryo-EM) and cryo-electron tomography (cryo-ET), coupled with computational modeling, has enabled the creation of integrative 3D models of viruses, bacteria, and cellular organelles. These models, composed of thousands of macromolecules and billions of atoms, have historically posed significant challenges for manipulation and visualization without specialized molecular graphics tools and hardware. With the recent advancements in GPU rendering power and web browser capabilities, it is now feasible to render interactively large molecular scenes directly on the web. In this work, we introduce Mesoscale Explorer, a web application built using the Mol* framework, dedicated to the visualization of large-scale molecular models ranging from viruses to cell organelles. Mesoscale Explorer provides unprecedented access and insight into the molecular fabric of life, enhancing perception, streamlining exploration, and simplifying visualization of diverse data types, showcasing the intricate details of these models with unparalleled clarity.

Impact of Households’ Future Orientation and Values on Their Willingness to Install Solar Photovoltaic Systems

Solar energy is increasing in popularity as a renewable energy source, which reduces greenhouse gas emissions. Even though many governments promote solar energy by giving various incentives, its adoption rate in households is slow. Psychological factors have been relatively overlooked in solar adoption, despite the importance of social and economic factors. Therefore, the purpose of this study is to investigate how psychological determinants impact households’ willingness to install solar photovoltaic (PV) systems. This study focusses on the future orientation and personal values (biospheric, altruistic, and egoistic values) of households’ and their willingness to install solar PV systems. The research draws from three environmental psychology theories: values orientation theory, value beliefs and norms theory, and the theory of planned behaviour to construct an integrative theoretical model. A survey involving 179 respondents in Australia was conducted and analysed applying the PLS-SEM technique. Findings revealed that future orientation and values are significant predictors of household willingness to install solar PV systems. Further, findings showed that attitude and perceived behavioural control play a significant role in installing solar. The findings will assist policymakers and solar companies in developing lucrative policies and marketing strategies to promote solar PV systems among households.

What can talent management do about involuntary remote working in the post-COVID-19 era? Spanish IT employees’ organizational commitment

The purpose of this study is to understand the role of professional isolation and work–family balance (WFB) as talent retention strategies, considering organizational commitment (OC) and the mediating role of job satisfaction (JS) among IT employees in the technological industry have been forced by their companies to telework. While previous research has examined the connections between professional isolation (PI), OC, WFB, and JS separately in the context of teleworking, this research proposes an integrative model examining the connections between all these work-related constructs and allowing for mediating and moderating effects. It focuses on IT employees in the technological industry forced to telework, a setting underexamined by previous literature. The final sample is composed of 294 teleworkers forced to work partly at home by their companies. Partial least squares structural equation modeling (PLS-SEM) was applied, and SmartPLS 4.0.8.7 software was used to analyze the data and test the hypotheses. Our results indicate a positive and significant direct effect of WFB on JS and OC, a negative and significant effect of PI on JS and OC, and a positive and significant effect of JS on OC. Our results also indicate that JS mediates the relationship between WFB and OC and between PI and OC and that neither time spent teleworking nor gender moderates the association between PI and OC. Overall, our results suggest that while PI negatively affects OC, JS, and WFB are the most relevant determinants of OC in the context of teleworking. In addition, a complementary IPMA analysis reinforces this view by suggesting that WFB and JS are the most important factors in determining OC performance among IT employees working from home, while PI is not important. The originality of this article is the proposal of an integrative model examining the connections between JS, WFB, PI, and OC and allowing for mediating (JS) and moderating (gender and percentage of time teleworking) effects from a talent management perspective. Moreover, this study focuses on information technology companies and the situation of forced remote working, two settings that have been underexamined. The results could help companies with forced teleworking develop effective strategies to attract, develop, and retain top talent in the information technology industry in the post-pandemic era. It is important for practitioners to consider the interactions between diverse work-related dimensions and the mediating and moderating effects between them to efficiently implement talent management strategies and reinforce OC and, in turn, economic performance.

Integrating Curriculum and Instruction In Islamic Religious Education : Insights from Robin Fogarty's Theory

This research explores strategies to enhance the coherence between curriculum and instruction in Islamic Religious Education (IRE) by employing Robins Fogarty's theory of curriculum integration. Utilizing a qualitative approach with integrating a theoretical study as a research design. Specifically, the study highlights the utility of Fogarty’s tripartite integration model as a critical lens for developing a unified IRE curriculum. This model aims to synchronize disparate content areas, fostering a more integrated and holistic student understanding. For the data sources, the research examined the various theories linked with Forgaty’s theory, and the data analysis was qualitative, in which the research tried to explain and integrate the theory into IRE policy. The findings from the study emphasized the imperative for further applied research to develop integrated lesson plans, explore teachers’ experiences and professional development needs, and assess comprehensive learning outcomes. The research advocates for a collaborative approach between curriculum theorists and educators to refine and advance IRE policies. Such collaborative efforts ensure that IRE promotes intellectual advancement and contributes to students’ spiritual and personal growth, ultimately enriching their educational experience.

α-Synuclein species in plasma neuron-derived extracellular vesicles as biomarkers for iRBD.

Isolated REM sleep behavior disorder (iRBD) is considered as the strongest predictor of Parkinson's disease (PD). Reliable and accurate biomarkers for iRBD detection and the prediction of phenoconversion are in urgent need. This study aimed to investigate whether α-Synuclein (α-Syn) species in plasma neuron-derived extracellular vesicles (NDEVs) could differentiate between iRBD patients and healthy controls (HCs). Nanoscale flow cytometry was used to detect α-Syn-containing NDEVs in plasma. A total of 54 iRBD patients and 53 HCs were recruited. The concentrations of total α-Syn, α-Syn aggregates, and phosphorylated α-Syn at Ser129 (pS129)-containing NDEVs in plasma of iRBD individuals were significantly higher than those in HCs (p < 0.0001 for all). In distinguishing between iRBD and HCs, the area under the receiver operating characteristic (ROC) curve (AUC) for an integrative model incorporating the levels of α-Syn, pS129, and α-Syn aggregate-containing NDEVs in plasma was 0.965. This model achieved a sensitivity of 94.3% and a specificity of 88.9%. In iRBD group, the concentrations of α-Syn aggregate-containing NDEVs exhibited a negative correlation with Sniffin' Sticks olfactory scores (r = -0.351, p = 0.039). Smokers with iRBD exhibited lower levels of α-Syn aggregates and pS129-containing NDEVs in plasma compared to nonsmokers (pα-Syn aggregates = 0.014; ppS129 = 0.003). The current study demonstrated that the levels of total α-Syn, α-Syn aggregates, and pS129-containing NDEVs in the plasma of individuals with iRBD were significantly higher compared to HCs. The levels of α-Syn species-containing NDEVs in plasma may serve as biomarkers for iRBD.

How much do family‐supportive supervisor behaviours matter? A meta‐analysis based on the ability‐motivation‐opportunity framework

AbstractFamily‐supportive supervisor behaviours (FSSB) and their association with employees' work, family, and health outcomes have been widely investigated in workplace contexts. We aimed to acquire a comprehensive understanding of whether FSSB have valuable associations with work, family, and health outcomes and to investigate how FSSB are related to these outcomes using 126 independent samples retrieved from 122 articles (N = 59,068). Our findings revealed several outcomes. First, the bivariate results demonstrated that FSSB were significantly associated with essential work, family, and health outcomes. Second, FSSB exerted beneficial incremental effects on task performance, burnout, organizational commitment, and job satisfaction beyond coworker support, flexible work arrangements, and family‐supportive organizational perceptions, providing further support for its discriminant validity. Third, we built an integrative model that uses ability‐motivation‐opportunity as our organizational framework. Our findings demonstrate that FSSB are significantly associated with employees' work and health outcomes through self‐efficacy, intrinsic motivation, and autonomy. Intrinsic motivation exerts the largest mean indirect effect, followed by self‐efficacy and autonomy. Based on these findings, we discuss theoretical and practical implications as well as directions for future research.

Digital platforms and the construction supply chain: trends and emerging themes in extant AEC research

A substantial body of research has emerged on the conditions that impact how and when industry stakeholders adopt digital platforms. However, in the construction industry in general—and the architecture, engineering and construction (AEC) industry in particular—to date, this research remains fragmented, which hampers our understanding of how digital platforms can enhance productivity and value creation. This paper aims to provide a better understanding of the benefits and challenges of adopting digital platforms and integrating them into the AEC industry. We conduct a systematic literature review on digital platform integration to identify themes that are relevant to the AEC industry. Based on our findings, we develop an integrative model that captures the phases of digital platform adoption and integration and outlines where different industry stakeholders tend to face challenges in this process, and we pinpoint where benefits can be derived. We employ this model to derive a research agenda that will fill the identified knowledge gaps currently existing in our understanding of construction industry stakeholders’ integration within the digital platform space.

Impact of Cloud Vertical Overlap on Cloud Radiative Effect in the Korean Integrated Model (KIM) Seasonal Simulations during Boreal Summer and Winter

AbstractExponential-random vertical overlap of clouds is applied for radiative processes in a research version of the Korean Integrated Model (KIM) to replace the maximum-random vertical overlap of clouds. The cloud radiative effect (CRE) increases overall when the exponential-random overlap is used. This is because vertically continuous clouds, which are assumed to overlap maximally under the maximum-random overlap assumption, can be relaxed to random overlap depending on the vertical distance between cloud layers and the specified decorrelation length of clouds. CRE is more enhanced by considering the latitudinal dependency of cloud decorrelation length based on previous observational studies. This alleviates biases in CRE, which is underestimated overall, except in the low latitudes where the CRE is overestimated in the present simulations. The interaction between radiative and convective processes plays a role in decreasing CRE over the tropical western Pacific region, where strong convections develop, although the direct impact of applying the exponential-random overlap is to decrease the vertical overlap between ice clouds. The simulation of temperature in the lower troposphere is improved owing to the changes in cloud overlap. The warm bias over the Eurasian continent, in particular, is alleviated as more shortwave fluxes are reflected due to increased CRE.

Models and P4R asset description for digital twin-based advanced planning and scheduling using cyber-physical integration for resilient production operation

Advanced planning and scheduling (APS) addresses the complex and uncertain nature of production control. A digital twin (DT), which incorporates simulations through cyber-physical integration, provides an advanced functionality for APS. To facilitate efficient design and implementation, a DT-based APS must satisfy three requirements: technical functionalities for resilience, robust models for diverse operational constraints, and efficient interoperability through cyber-physical integration. Although several studies have proposed the use of DT as a primary technology for APS, proposals that address the process, functionality, integration, and information models are lacking. Additionally, the existing asset descriptions cannot adequately capture the sophisticated characteristics of DT and necessary informational elements for APS. Thus, this study designed a process model, functionalities, and integration models for the DT-based APS and asset descriptions for snapshot synchronization. Crucial service-compositions and functionalities were defined using work-center-level lifecycles. Consequently, a process model was developed, which focused on core activities for resilience. Moreover, horizontal integration between DT and control functionalities and vertical integration between DT and standards, were proposed to enhance the DT-based APS. The proposed method effectively managed the product, process, plan, plant, and resource classes by ensuring adherence to asset administration shell principles. To validate the effectiveness of the proposed methods, two work centers with distinctly different characteristics were employed and demonstrated dominant preventive measures compared to static functionality-based methods. The primary contributions encompass the facilitation of integration and interoperability within a DT-based APS. The proposed methods support the advanced characteristics of DT, ensuring robustness and neutrality across heterogeneous operational contexts.

Multi-omics analysis reveals regime shifts in the gastrointestinal ecosystem in chickens following anticoccidial vaccination and Eimeria tenella challenge.

Coccidiosis, caused by Eimeria parasites, significantly impacts poultry farm economics and animal welfare. Beyond its direct impact on health, Eimeria infection disrupts enteric microbial populations leading to dysbiosis and increases vulnerability to secondary diseases such as necrotic enteritis, caused by Clostridium perfringens. The impact of Eimeria infection or anticoccidial vaccination on host gastrointestinal phenotypes and enteric microbiota remains understudied. In this study, the metabolomic profiles and microbiota composition of chicken caecal tissue and contents were evaluated concurrently during a controlled experimental vaccination and challenge trial. Cobb500 broilers were vaccinated with a Saccharomyces cerevisiae-vectored anticoccidial vaccine and challenged with 15,000 Eimeria tenella oocysts. Assessment of caecal pathology and quantification of parasite load revealed correlations with alterations to caecal microbiota and caecal metabolome linked to infection and vaccination status. Infection heightened microbiota richness with increases in potentially pathogenic species, while vaccination elevated beneficial Bifidobacterium. Using a multi-omics factor analysis, data on caecal microbiota and metabolome were integrated and distinct profiles for healthy, infected, and recovering chickens were identified. Healthy and recovering chickens exhibited higher vitamin B metabolism linked to short-chain fatty acid-producing bacteria, whereas essential amino acid and cell membrane lipid metabolisms were prominent in infected and vaccinated chickens. Notably, vaccinated chickens showed distinct metabolites related to the enrichment of sphingolipids, important components of nerve cells and cell membranes. Our integrated multi-omics model revealed latent biomarkers indicative of vaccination and infection status, offering potential tools for diagnosing infection, monitoring vaccination efficacy, and guiding the development of novel treatments or controls.IMPORTANCEAdvances in anticoccidial vaccines have garnered significant attention in poultry health management. However, the intricacies of vaccine-induced alterations in the chicken gut microbiome and its subsequent impact on host metabolism remain inadequately explored. This study delves into the metabolic and microbiotic shifts in chickens post-vaccination, employing a multi-omics integration analysis. Our findings highlight a notable synergy between the microbiome composition and host-microbe interacted metabolic pathways in vaccinated chickens, differentiating them from infected or non-vaccinated cohorts. These insights pave the way for more targeted and efficient approaches in poultry disease control, enhancing both the efficacy of vaccines and the overall health of poultry populations.

Интернет-игровое расстройство и неудовлетворенные психологические потребности: опосредующая роль самооценки, депрессии и эскапизма

&lt;p&gt;Internet gaming disorder (IGD) is a widespread mental health issue especially among youth but its etiology remains unclear. The aim of this study was to test an integrative path model in which basic universal psychological needs of competence, autonomy, and relatedness predict IGD through the serial mediation of self-esteem, depression, and escape motivation. Study design was cross-sectional. A total of 331 Turkish gamers whose mean age was 22.7 years (SD=4.73) were recruited through purposive sampling. Among the participants, 57.1% (n=189) were male and 42.9% (n=142) were female. Online standardized self-report questionnaires for measuring IGD, gaming motivations, basic psychological needs satisfaction, self-esteem, and depression were filled out by the participants. In this regard, a personal information form, the Internet Gaming Disorder Scale-Short Form, Motives for Online Gaming Questionnaire, Basic Psychological Need Satisfaction Scale-In General, Rosenberg Self-Esteem Scale, and the Hospital Anxiety Depression Scale-Depression Subscale were administered. Men had higher mean IGD and gaming motivations scores compared to women. It was found that self-esteem, depression, and escapism serially mediated the association between basic psychological needs and IGD. The contribution of the findings to the relevant literature and clinical implications were discussed.&lt;/p&gt;

Assessing carbon capture and storage technology in industrial joint venture

Carbon Capture and Storage (CCS) technology can effectively reduce carbon dioxide emissions from industrial and energy production processes. Yet the commercialization of CCS technology is hampered by financial requirements. Existing research compares the costs and benefits of business models for individual CCS projects, no studies assess the industry and national levels. Here we use a dynamic computable general equilibrium model, constructure the vertical integration and joint venture business models for CCS. This study assesses the emission and economic impacts of joint ventures between China's high-emission industries and their upstream and downstream sectors. We find that adopting the joint venture model in the coal power sector, compared to the vertical integration model, initially exerts a negative economic impact but can mitigate 0.04 % of GDP by 2060. The chemical industry consistently benefits from the joint venture model both economically and in emission reductions. Downstream sectors of the steel and cement industries are unsuitable for participation in joint ventures. In addition, the joint venture model has significant industry linkage effects, affecting energy consumption, the scale and cost of CCS deployment. This work provides important information for the large-scale commercialization of CCS technology.

A novel multiscale cGAN approach for enhanced salient object detection in single haze images

In computer vision, image dehazing is a low-level task that employs algorithms to analyze and remove haze from images, resulting in haze-free visuals. The aim of Salient Object Detection (SOD) is to locate the most visually prominent areas in images. However, most SOD techniques applied to visible images struggle in complex scenarios characterized by similarities between the foreground and background, cluttered backgrounds, adverse weather conditions, and low lighting. Identifying objects in hazy images is challenging due to the degradation of visibility caused by atmospheric conditions, leading to diminished visibility and reduced contrast. This paper introduces an innovative approach called Dehaze-SOD, a unique integrated model that addresses two vital tasks: dehazing and salient object detection. The key novelty of Dehaze-SOD lies in its dual functionality, seamlessly integrating dehazing and salient object identification into a unified framework. This is achieved using a conditional Generative Adversarial Network (cGAN) comprising two distinct subnetworks: one for image dehazing and another for salient object detection. The first module, designed with residual blocks, Dark Channel Prior (DCP), total variation, and the multiscale Retinex algorithm, processes the input hazy images. The second module employs an enhanced EfficientNet architecture with added attention mechanisms and pixel-wise refinement to further improve the dehazing process. The outputs from these subnetworks are combined to produce dehazed images, which are then fed into our proposed encoder–decoder framework for salient object detection. The cGAN is trained with two modules working together: the generator aims to produce haze-free images, whereas the discriminator distinguishes between the generated haze-free images and real haze-free images. Dehaze-SOD demonstrates superior performance compared to state-of-the-art dehazing methods in terms of color fidelity, visibility enhancement, and haze removal. The proposed method effectively produces high-quality, haze-free images from various hazy inputs and accurately detects salient objects within them. This makes Dehaze-SOD a promising tool for improving salient object detection in challenging hazy conditions. The effectiveness of our approach has been validated using benchmark evaluation metrics such as mean absolute error (MAE), peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM).