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This study aims to examine the positive impact of strategies on the viability of small and medium-sized enterprises (SMEs) in times of crisis. Specifically, it investigates the influence of resource utilization as an initial survival strategy on innovation practices and SMEs’ performance. It further assesses the potential impact of government aid and partnerships on the relationship between resource utilization and innovation.

This study used a mixed-method approach that integrates phenomenology and quantitative research. This phenomenological study conducted in-depth interviews with 23 SME owners. Based on qualitative findings, a quantitative research design was developed, and this study surveyed 352 SMEs. Structural equation modeling was used for hypothesis testing.

Resource utilization as an initial survival strategy has a positive effect on increasing organizational innovation practices and ultimately affects business performance. Furthermore, government support and external partnerships significantly enhance the relationship between resource utilization and innovation.

The COVID-19 pandemic brought a crisis for businesses but has provided many positive transformations. SME entrepreneurs should sustain their survival strategies and seize external support to enhance their potential. Due to the pandemic, various efforts have created innovations, honed business resiliency and increased competitiveness.

SMEs struggled with the crisis and responded by utilizing many retrenchment strategies. This study is among the first to provide empirical evidence of an emergency response that has resulted in fruitful impacts. The findings can be generalized to represent the behavior of SMEs, especially in emerging countries.

Reading habit plays a pivotal role in individuals' personal and academic growth, making it essential to encourage among campus users. University libraries serve as valuable platforms to promote reading by providing access to a diverse range of books and resources. Recommending books through personalized systems not only helps campus users discover new materials but also enhances their engagement and satisfaction with the library’s offerings, contributing to a holistic learning experience.

This study presents a web-based solution, the Web-Based Hybrid Intelligent Book Recommender System (W_HybridBook), as a solution that addresses challenges like cold start issues and limited scalability by factoring in user preferences and item similarities in generating book recommendations. The paper improves the traditional hybrid system using Genre-Oriented Profiles (GOPs) instead of original rating profiles of users when determining similarities between individuals. Consumption-based genre profiles (W_HybridBook-CBP) are created by assessing whether an item has received any ratings in the dataset, and vote-based genre profiles (W_HybridBook-VBP) are generated by considering the genre categories based on the magnitude of the user’s rating.

The comparative results indicated that users are quite satisfied with the recommendations generated by W\_HybridBook-VBP profiling, with an average rating of 4.0633 and a precision value of 0.7988. W\_HybridBook-VBP is also the fastest way with respect to the algorithm and recommendation run time.

The proposed W\_HybridBook has been then enhanced by adopting two user profiling strategies to boost the similarity calculation process in the recommendation generation phase. This system provides ranking-based recommendations by mainly integrating well-known collaborative and content-based filtering strategies. A dataset has been collected by considering the preferences of both users and academics at Izmir Bakircay University, which is one of the universities with the highest number of books per student. More importantly, this dataset has been released and become publicly available for future research in the recommender system field.

This study seeks to develop an Environmental Sustainability Balanced Scorecard (ESBSC) articulated through a strategic map for collaborative implementation by municipalities by municipalities. In addition, it aims to elucidate the architecture of this tool.

The research uses qualitative methodology, initiating with document analysis, followed by municipal-level surveys and an interview with the Norte Portugal Regional Coordination and Development Commission (CCDR-N).

The study constructs an ESBSC that adopts an integrative approach to sustainability, focusing on municipal joint action. The tool fosters synergies and enhances cooperation. By incorporating a strategic mix, the tool contributes to improving the environmental management performance of the participating municipalities.

This study introduces a tool designed for municipalities that aspire to incorporate environmental sustainability into their strategies. This tool facilitates the implementation and management of a long-term environmental strategy, with potential implications for organization and its culture. In addition, it highlights critical environmental factors that should serve as a starting point in future studies or applications of this tool.

Involving both an academic institution and multiple municipalities, this research identifies critical environmental factors that enhance environmental awareness within municipalities and designs a tool that, when consciously adopted, can influence the culture dynamics of the population involved. Furthermore, it proposes a structured and systematic research method for creating an ESBSC for joint municipal action.

To the best of authors’ knowledge, this research constitutes the first exploratory attempt to devise an environmental strategy for joint municipal action. Although the tool emphasizes the environmental component, it promotes an integrated vision of sustainability. Despite the extensive application of balanced scorecards in various organizational contexts, their utilization in fostering environmental sustainability at a municipal level remains underexplored. This study addresses this gap by developing a tailored strategic tool that operationalizes environmental priorities within municipal governance frameworks.

This paper aims to (1) identify the different performance drivers (lead indicators) and outcome measures (lag indicators) investigated in the literature concerning the four balanced scorecard (BSC) perspectives in operations management (OM) contexts and (2) understand how performance drivers and outcome measures (and substantiated perspectives) are related.

We undertake a systematic literature review of the BSC literature in OM journals. From the final sample of 40 articles, performance drivers and outcome measures have been identified, and the relationships amongst them have been synthesised according to the system dynamics approach.

Findings show (1) the most relevant performance drivers and outcome measures within each BSC perspective, (2) their relationships, (3) how the perspectives are linked through the performance drivers and outcome measures and (4) how the different measures relate systemically. Accordingly, four causal loops amongst identified measures have been built, which – jointly considered – allowed for the creation of a dynamic strategy map for OM.

This study is the first one that provides a comprehensive and holistic view of how the different performance drivers and outcome measures within and between the four BSC perspectives in OM relate systemically, increasing the knowledge and understanding of scholars and practitioners.

Circular building adaptability (CBA) in adaptive reuse – building transformation – projects can facilitate a resource-efficient and futureproof redevelopment of the built environment. However, there has been a lack of practical tools that guide practitioners on how to foster CBA in adaptive reuse. Therefore, this study aims to collaboratively develop a guiding framework for CBA in adaptive reuse (CBA-AR) projects in general. The CBA-AR framework is a descriptive and content-oriented synthesis mapping a series of strategies to the CBA determinants alongside their enablers and inhibitors.

A participatory research-oriented approach was followed. First, an archival research was conducted to develop the CBA-AR framework based on literature review and case studies. Second, two co-creation workshops, triangulated with structured interviews, were conducted to validate and expand the framework.

The first version of the CBA-AR framework comprises 30 CBA strategies. It also brings seven enablers and six inhibitors together with the 30 CBA strategies. The outcomes of the participatory approach contributed to refining and expanding the framework. The final of the CBA-AR framework version comprises CBA 33 strategies. This version brings 10 enablers and 7 inhibitors together with the 33 strategies.

This framework can be used as a guiding and reporting instrument by designers and property developers while transforming vacant or obsolete properties in the Netherlands. Policy makers can refer to this framework and amend adaptive reuse legislation.

The CBA-AR framework can introduce a transformative change in theory and practice, as it is based on theoretical, empirical and participatory research.

The present study aims to identify significant barriers to adopting prefabricated construction (PFC) in developing economies using a study in Sri Lanka and develop an integrated strategy framework to mitigate and overcome the obstacles.

The research process included a comprehensive literature review, a pilot study, a questionnaire survey for data collection, statistical analysis and a qualitative content analysis.

Ranking method revealed that all 23 barriers were significant. Top significant barriers include challenges in prefabricated component transportation, high capital investment costs and lack of awareness of the benefits of PFC among owners/developers. Factor analysis clustered six barrier categories (BCs) that fit the barrier factors, explaining 71.22% of the cumulative variance. Fuzzy synthetic evaluation revealed that all BCs significantly influence PFC adoption in Sri Lanka. Finally, the proposed mitigation strategies were mapped with barriers to complete the integrated framework.

The study outcomes are relevant to construction industry stakeholders of Sri Lanka, who are keen to enhance construction efficiencies. The implications can also benefit construction industry stakeholders and policymakers to formulate policies and regulations and identify mitigation solutions.

The study provides deeper insights into the challenges to adopting prefabrication in South Asian countries such as Sri Lanka. Furthermore, the integrated framework is a novel contribution that can be used to derive actions to mitigate barriers in developing economies.

The pressing issues of climate change and environmental degradation call for a reevaluation of how we approach economic activities. Both leaders and corporations are now shifting their focus, toward adopting practices and embracing the concept of circular economy (CE). Within this context, the Food and Beverage (F&B) sector, which significantly contributes to greenhouse gas (GHG) emissions, holds the potential for undergoing transformations. This study aims to explore the role that Artificial Intelligence (AI) can play in facilitating the adoption of CE principles, within the F&B sector.

This research employs the Best Worst Method, a technique in multi-criteria decision-making. It focuses on identifying and ranking the challenges in implementing AI-driven CE in the F&B sector, with expert insights enhancing the ranking’s credibility and precision.

The study reveals and prioritizes barriers to AI-supported CE in the F&B sector and offers actionable insights. It also outlines strategies to overcome these barriers, providing a targeted roadmap for businesses seeking sustainable practices.

This research is socially significant as it supports the F&B industry’s shift to sustainable practices. It identifies key barriers and solutions, contributing to global climate change mitigation and sustainable development.

The research addresses a gap in literature at the intersection of AI and CE in the F&B sector. It introduces a system to rank challenges and strategies, offering distinct insights for academia and industry stakeholders.

This paper proposes a self-supervised monocular depth estimation algorithm under multiple constraints, which can generate the corresponding depth map end-to-end based on RGB images. On this basis, based on the traditional visual simultaneous localisation and mapping (VSLAM) framework, a dynamic object detection framework based on deep learning is introduced, and dynamic objects in the scene are culled during mapping.

Typical SLAM algorithms or data sets assume a static environment and do not consider the potential consequences of accidentally adding dynamic objects to a 3D map. This shortcoming limits the applicability of VSLAM in many practical cases, such as long-term mapping. In light of the aforementioned considerations, this paper presents a self-supervised monocular depth estimation algorithm based on deep learning. Furthermore, this paper introduces the YOLOv5 dynamic detection framework into the traditional ORBSLAM2 algorithm for the purpose of removing dynamic objects.

Compared with Dyna-SLAM, the algorithm proposed in this paper reduces the error by about 13%, and compared with ORB-SLAM2 by about 54.9%. In addition, the algorithm in this paper can process a single frame of image at a speed of 15–20 FPS on GeForce RTX 2080s, far exceeding Dyna-SLAM in real-time performance.

This paper proposes a VSLAM algorithm that can be applied to dynamic environments. The algorithm consists of a self-supervised monocular depth estimation part under multiple constraints and the introduction of a dynamic object detection framework based on YOLOv5.

Engineering graduates are expected to have certain attributes in addition to technical expertise that includes development in personal and interpersonal skills with societal concern. Pedagogical strategies have been continuously evolving to improve the graduate attributes. An efficient framework for blended learning that improves the graduate attributes is the need of the hour now.

A blended course model based on TPACK is proposed and the same is evaluated with Kirkpatrick evaluation method to assess the attainment of the attributes. A mapping strategy is developed for the relation between course outcomes and graduate attributes. The proposed model is tested with “Microcontroller” course in undergraduate program with students of three consecutive years in three different learning environments: offline, online and blended. The performance of the students in assessments, students’ feedback and their interest towards additional learning, project skills and job recruitment are the different elements taken for analysis.

The results obtained show that the impact of the proposed blended learning framework in improving the graduate attributes is greater than the offline environments. The analysis is done based on Kirkpatrick evaluation, which demonstrates the improvement in graduate attributes in blended learning by 18% compared to offline mode.

It is seen that blended learning shall be implemented using TPACK model effectively and the proposed model results in improvement of graduate attributes. Though the findings are good enough, the case study is limited to a particular organization and so, the various underlying parameters may vary for different institutions.

The methodology proposed is viable in any institution and may be tested for any program. The effectiveness of the blended learning is known and in this case study, the analysis from the course to the level of program is done.

The research work highlights the integration of technology, pedagogy and content knowledge to enhance engineering students' skills. Hence, it explores a new required norms of education, potentially shaping future teaching learning methodologies. By employing the Kirkpatrick evaluation, it offers insights into the model's effectiveness and influences educational practices in the need of the hour.

The proposed method and results signifies an innovative endeavor that combines technological expertise, pedagogical methods and subject matter knowledge to enhance the attributes of engineering graduates. Kirkpatrick evaluation adds a distinct dimension by objectively assessing the model's impact. The results are analyzed from the original data obtained from a particular institution.

This study examines the use of a dynamic value-based approach to analyze the business model structuration of smart service providers in Brazil, mapping their value creation, configuration and appropriation strategies, and determining how well-defined their current business models are.

This is a qualitative study based on semi-structured interviews with entrepreneurs (or CEOs and directors of technology) of seven business ventures in three different phases of business model structuration: (1) academic: companies or innovation and research centers linked to universities; (2) startups: technology-based companies originating from the technological needs of clients, be they new branches of the traditional business of incumbents or new entrants and (3) autonomous service providers whose offerings are related to master’s or doctoral projects.

We propose a typology of business model structuration with four stages. At first (individual or initial business model), albeit with high skilling of owners, only manual or adaptation services are offered. In the second stage (platform business model), although services offered are oriented toward the entire process automatization of the client (Factory integrated), technologies are restricted to the client company (or even one department) and these clients' needs are mainly data processing and connectivity. In the third stage (scaling digital business model), although the services offered are oriented toward greater digitalization through an entire array of field devices connected to the internet (IoT) and organized in a more formalized structure, the business model is still being constructed, companies in this stage are mainly startups. In the fourth stage (innovation ecosystem business model), the entire manufacturing process is digitized, with integration and network connectivity, both between service providers and the extended supply chain of their clients, and new technologies are customized and developed through the interaction of a whole innovation ecosystem.

Mapping value-based strategies aids in understanding business model structuration in Industry 4.0. Future research should focus on parameterizing the dimensions founded of each value strategy.

This study advances the comprehension of the business model in |Industry 4.0 by providing a value-based strategy perspective of business model structuration. Practically, by focusing on smart service providers, it contributes to a greater understanding of smart service providers in Brazil and their strategic challenges.