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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.

Existing labor estimation models typically consider only certain construction project types or specific influencing factors. These models are focused on quantifying the total labor hours required, while the utilization rate of the labor during the project is not usually accounted for. This study aims to develop a novel machine learning model to predict the time series of labor resource utilization rate at the work package level.

More than 250 construction work packages collected over a two-year period are used to identify the main contributing factors affecting labor resource requirements. Also, a novel machine learning algorithm – Recurrent Neural Network (RNN) – is adopted to develop a forecasting model that can predict the utilization of labor resources over time.

This paper presents a robust machine learning approach for predicting labor resources’ utilization rates in construction projects based on the identified contributing factors. The machine learning approach is found to result in a reliable time series forecasting model that uses the RNN algorithm. The proposed model indicates the capability of machine learning algorithms in facilitating the traditional challenges in construction industry.

The findings point to the suitability of state-of-the-art machine learning techniques for developing predictive models to forecast the utilization rate of labor resources in construction projects, as well as for supporting project managers by providing forecasting tool for labor estimations at the work package level before detailed activity schedules have been generated. Accordingly, the proposed approach facilitates resource allocation and enables prioritization of available resources to enhance the overall performance of projects.

This study aims to examine the participants’ [junior high school students and Master of business administration (MBA) consultants] perceptions and utilizations of the multidimensional place-based resources within the context of Education for Sustainable Development (ESD), specifically focusing on its alignment with the sustainable development goals (SDGs) for quality education. While place-based resources have demonstrated the potential for fostering innovative thinking and collaborative efforts, a gap exists in understanding how these resources can be effectively integrated to bolster learning and sustainable outcomes.

The authors adopted a single-case research methodology and conducted an in-depth exploration of the integration of place-based resources within the context of ESD using the 2021 Forest Community Outreach (FCO) Project in Ena City, Japan. Questionnaires, daily journals and consultation reports were used for data collection. This study used the coding and qualitative content analysis process to understand the significance of the five dimensions of place-based resources in fostering effective ESD practices.

The findings show the gap between interest in ESD and utilization of place-based resources as reflected in the perceptions and interests of junior high school participants. MBA consultants acknowledged the relevance of leveraging the five dimensions of place-based resources in the context of ESD. This research enriches the understanding of recognizing and harnessing different resources within the settings, emphasizing the significance of a multidimensional place-based resources approach to effectively incorporate these resources into ESD, thereby fostering learning and practical sustainability outcomes.

This study conducts a novel analysis of diverse dimensions within the realm of place-based resources and their profound influence on the learning experiences and creativity of participants engaged in ESD. The study lays the groundwork for the validation of place-based resource dimensions through collaborative efforts involving stakeholders within the region.

Precast wall lifting during prefabricated building construction faces multiple non-lean problems, such as inaccurate lifting-time estimation, unreasonable resource allocation and improper process design. This study aims to identify the pathways for improving lifting performance to advance lean construction of prefabricated buildings.

This study developed a methodological framework that integrates the discrete event simulation method, the elimination, combination, rearrangement and simplification (ECRS) technique and intelligent optimization tool. Two schemes of precast wall lifting, namely, the enterprise's business as usual (BAU) and enterprise-leading (EL) schemes, were set to benchmark lifting performance. Furthermore, a best-practice (BP) scheme was modeled from the perspective of lifting activity ECRS and resource allocation for performance optimization.

A real project was selected to test the effect of the methodological framework. The results showed that compared with the EL scheme, the BP scheme reduced the total lifting time (TLT) by 6.3% and mitigated the TLT uncertainty (the gap between the maximum and minimum time values) by 20.6%. Under the BP scheme, increasing the resource inputs produces an insignificant effect in reducing TLT, i.e. increasing the number of component operators in the caulking subprocess from one to two only shortened the TLT by 3.6%, and no further time reduction was achieved as more component operators were added.

To solve non-lean problems associated with prefabricated building construction, this study provides a methodological framework that can separate a typical precast wall lifting process into fine-level activities. Besides, it also identifies the pathways (including the learning effect mitigation, labor and machinery resource adjustment and activities’ improvement) to reducing TLT and its uncertainty.

The target of this research is to develop a mathematical model which combines the Resource-Constrained Multi-Project Scheduling Problem (RCMPSP) and the Multi-Skilled Resource-Constrained Project Scheduling Problem (MSRCPSP). Due to the importance of resource management, the proposed formulation comprises resource leveling considerations as well. The model aims to simultaneously optimize: (1) the total time to accomplish all projects and (2) the total deviation of resource consumptions from the uniform utilization levels.

The K-Means (KM) and Fuzzy C-Means (FCM) clustering methods have been separately applied to discover the clusters of activities which have the most similar resource demands. The discovered clusters are given to the scheduling process as priori knowledge. Consequently, the execution times of the activities with the most common resource requests will not overlap. The intricacy of the problem led us to incorporate the KM and FCM techniques into a meta-heuristic called the Bi-objective Symbiosis Organisms Search (BSOS) algorithm so that the real-life samples of this problem could be solved. Therefore, two clustering-based algorithms, namely, the BSOS-KM and BSOS-FCM have been developed.

Comparisons between the BSOS-KM, BSOS-FCM and the BSOS method without any clustering approach show that the clustering techniques could enhance the optimization process. Another hybrid clustering-based methodology called the NSGA-II-SPE has been added to the comparisons to evaluate the developed resource leveling framework.

The practical importance of the model and the clustering-based algorithms have been demonstrated in planning several construction projects, where multiple water supply systems are concurrently constructed.

Reviewing the literature revealed that there was a need for a hybrid formulation that embraces the characteristics of the RCMPSP and MSRCPSP with resource leveling considerations. Moreover, the application of clustering algorithms as resource leveling techniques was not studied sufficiently in the literature.

Bootstrapping is a practitioner-based term adopted in entrepreneurship to describe the techniques employed in micro, small and medium-sized enterprises (MSMEs) to minimise the need for external funding by securing resources at little or no cost and applying strategies to effectively use resources. Working capital management (WCM) is a term used in financial management to define a set of practices used to manage business resources, including cash management. This paper explores the overlap and divergence between these two disciplinary distinct concepts.

A dual methodology is employed. First, the usage of the two terms in prior literature is analysed and synthesised. Second, the study uses factor analysis to explore how bootstrapping practices described by owners of 167 established MSMEs relate to the components of WCM in financial management.

The factor analysis identifies two main bootstrapping practices employed by MSMEs: (1) delaying payments and owner-related bootstrapping and (2) customer-related bootstrapping. Delaying payments is an integral practice in trade payables management and customer-related bootstrapping includes practices that are integral to trade receivables management. Therefore, links between bootstrapping practices and WCM practices are firmly established.

The study is not without limitations. Based on cross-sectional evidence for established firms in Ireland only, future studies could explore cross-country longitudinal panel data to fully examine life cycle and sectoral effects, as well as other external shocks (for example, COVID-19) on bootstrapping and WCM practices. This study does not explain why some factors (for example, joint utilisation and inventory management) are present in some bootstrapping studies and not in others; further case study research might help explain this. Finally, changes in the business environment facing start-ups and established enterprise, including increased digitalisation, online trading, self-employment, remote hub working and sustainability, offer new avenues for bootstrapping research.

This is the first study to comprehensively explore the conceptual and empirical links between bootstrapping and WCM. This study will enable researchers and practitioners in these two distinct disciplines to learn from each other. Accounting researchers and practitioners can broaden their understanding of how WCM “works” in MSME settings. Similarly, entrepreneurship researchers and practitioners can deepen their understanding of how bootstrapping can be adopted by businesses to manage resources effectively.

The study attempts to explore the effectiveness of green supply chain strategies (GSCS) and sustainable practices (SP) in achieving a circular supply chain (CSC) within a business-to-business (B2B) context. The study further investigates the moderating role of green innovation (GIN) on the relationship between GSCS and SP.

The conceptual model was developed by adopting constructs from the existing studies. A self-administered tool was created, and data were gathered from supply chain (SC) specialists in the food, energy, tire, textile and paper industries. The structural equation model was employed to test the hypothesis, analyzing 243 responses obtained.

The findings indicate an affirmative association between GSCS, SP and the achievement of CSC, with SP acting as a partial mediator between GSCS and CSC. Results show that GSCS and SP are crucial for transitioning toward a circular model in the SC, emphasizing resource regeneration and sustainability. The data from our sample suggest that GIN significantly moderates the relationship between GSCS and CSC. These insights underline the importance of green strategies and sustainable practices (SP) in fostering CSCs in a B2B setting. The study’s implications are significant for SC management, suggesting that firms must integrate green and SP to achieve circularity and long-term viability.

This article brings forward a distinctive perspective on sustainability within the field of SC management emphasizing the crucial need for implementing CSC and GSCS in a B2B context.

This study aims to conceptualize and measure strategic leadership capabilities within research and development (R&D) teams pursuing high-tech innovation at public-funded R&D organizations in India.

A rigorous five-stage multi-method approach defines, conceptualizes and validates the core construct “strategic leadership capabilities for innovation” (SLCI). The first stage correlates the insights generated from theoretical analysis and expert opinions on the importance of leadership for innovation. The second study identifies a three-dimensional factor structure underlying the SLCI construct and the third validates it through a confirmatory factor analysis. Replication provides additional validation.

SLCI emerges as a three-dimensional construct with sub-dimensions: dynamic envisioning, ambidextrous resource utilization and empowering support for innovation.

Conceptualization of the SLCI construct and its measurement through a 15-item scale that has been empirically validated in the public-funded R&D organizations in India.

The extant literature emphasizes that the perspective of bricolage is significantly augmenting the core of entrepreneurship research, and, per se, it has made considerable contributions to understanding resource mobilization and organizational processes in entrepreneurial ventures. Entrepreneurial bricolage literature lacks a unified and holistic conceptual framework that could represent a coherence of diverse bricolage forms and their related capabilities in entrepreneurship. To address this issue, this study aims to develop a comprehensive typology framework of entrepreneurial bricolage based on the theoretical synthesis of the prior research.

By comparing and synthesizing the existing bricolage forms into a holistic and persistent typology, the authors present an integrated framework of 13 bricolage capabilities that contributes to resource acquisition and resource mobilization as well as facilitate the entrepreneurial processes of opportunity recognition and opportunity exploitation in firms.

The study synthesizes a wide array of research on entrepreneurial bricolage for shaping the resource acquisition and resource mobilization processes in entrepreneurial ventures and presents a typology-based framework for further discussion and research. By mapping the existing research and relevant dimensions into a typology-based entrepreneurial bricolage framework, the study extends and contributes to the current theorizing and conceptual building.

The study would help practitioners and researchers to recognize bricolage capabilities and the common ties among them, leading to further advances in entrepreneurship theory and practice.

As the body of knowledge regarding entrepreneurial bricolage has grown, so has the number of its different forms, concepts and constructs. The authors recognize that there is distinctiveness as well as overlaps among diverse forms, concepts and constructs of entrepreneurial bricolage. Further, the authors identify a new bricolage capability that has not until now been positioned in the extant frameworks.

This paper aims to examine the role of technological Innovation in ensuring resource sustainability in the water, energy and food (WEF) nexus, as there exists a shortage of statistical research on the extent of the influence of technological Innovation on the WEF nexus.

The study used a quantitative research method, using a well-structured questionnaire to collect data from management staff in the WEF departments in South Africa. The collected data were analyzed by using mean score ranking, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) for structural equation modelling (SEM).

The findings show that the technological process of technological innovation is significant for resource sustainability. The result also showed that technological innovations directly and statistically significantly affect WEF nexus. The EFA resulted in three components of WEF nexus product innovation, WEF nexus process innovation and WEF nexus novel innovations. Furthermore, the CFA and SEM analysis reveals that six technological innovation indicators influence the sustainability of the nexus: smart water metering technology, smart metering technology, food quality monitoring technology, agricultural technology solutions, new technological design and eco-friendly WEF products.

The sustainability of these three inevitable resources for man’s survival is dependent on technological innovations, and this study has shown the major categories of innovations needed, thus establishing a pathway for engineering design.