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Are there smart ways to find heuristics? What are the common principles behind heuristics? We propose an integrative definition of heuristics, based on insights that apply to all heuristics, and put forward meta-heuristics for discovering heuristics.

We employ Herbert Simon’s metaphor that human behavior is shaped by the scissors of the mind and its environment. We present heuristics from different domains and multiple sources, including scholarly literature, practitioner-reports and ancient texts.

Heuristics are simple, actionable principles for behavior that can take different forms, including that of computational algorithms and qualitative rules-of-thumb, cast into proverbs or folk-wisdom. We introduce heuristics for tasks ranging from management to writing and warfare. We report 13 meta-heuristics for discovering new heuristics and identify four principles behind them and all other heuristics: Those principles concern the (1) plurality, (2) correspondence, (3) connectedness of heuristics and environments and (4) the interdisciplinary nature of the scissors’ blades with respect to research fields and methodology.

We take a fresh look at Simon’s scissors-metaphor and employ it to derive an integrative perspective that includes a study of meta-heuristics.

This research aims to propose a model for the complex decision-making involved in the ecological restoration of mega-infrastructure (e.g. railway engineering). This model is based on multi-source heterogeneous data and will enable stakeholders to solve practical problems in decision-making processes and prevent delayed responses to the demand for ecological restoration.

Based on the principle of complexity degradation, this research collects and brings together multi-source heterogeneous data, including meteorological station data, remote sensing image data, railway engineering ecological risk text data and ecological restoration text data. Further, this research establishes an ecological restoration plan library to form input feature vectors. Random forest is used for classification decisions. The ecological restoration technologies and restoration plant species suitable for different regions are generated.

This research can effectively assist managers of mega-infrastructure projects in making ecological restoration decisions. The accuracy of the model reaches 0.83. Based on the natural environment and construction disturbances in different regions, this model can determine suitable types of trees, shrubs and herbs for planting, as well as the corresponding ecological restoration technologies needed.

Managers should pay attention to the multiple types of data generated in different stages of megaproject and identify the internal relationships between these multi-source heterogeneous data, which provides a decision-making basis for complex management decisions. The coupling between ecological restoration technologies and restoration plant species is also an important factor in improving the efficiency of ecological compensation.

Unlike previous studies, which have selected a typical section of a railway for specialized analysis, the complex decision-making model for ecological restoration proposed in this research has wider geographical applicability and can better meet the diverse ecological restoration needs of railway projects that span large regions.

The numerous spoil grounds brought about by mega transportation infrastructure projects which can be influenced by the ecological environment. To achieve better management of spoil grounds, this paper aims to assess their comprehensive risk levels and categorize them into different categories based on ecological environmental risks.

Based on analysis of the environmental characteristics of spoil grounds, this paper first comprehensively identified the ecological environmental risk factors and developed a risk assessment index system to quantitatively describe the comprehensive risk levels. Second, this paper proposed a comprehensive model to determine the risk assessment and categorization of spoil ground group in mega projects integrating improved projection pursuit clustering (PPC) method and K-means clustering algorithm. Finally, a case study of a spoil ground group (includes 50 spoil grounds) in a mega infrastructure project in western China is presented to demonstrate and validate the proposed method.

The results show that our proposed comprehensive model can efficiently assess and categorize the spoil grounds in the group based on their comprehensive ecological environmental risk. In addition, during the process of risk assessment and categorization of spoil grounds, it is necessary to distinguish between sensitive factors and nonsensitive factors. The differences between different categories of spoil grounds can be recognized based on nonsensitive factors, and high-risk spoil grounds which need to be focused more on can be identified according to sensitive factors.

This paper develops a comprehensive model of risk assessment and categorization of a group of spoil grounds based on their ecological environmental risks, which can provide a reference for the management of spoil grounds in mega projects.

The higher education sector plays an important role in a nation’s implementation of pro-environmental regulations. Environmental initiatives should be the focal point of a university's mission, and they are expected to be present in everyday academic life on campus. This study aims to propose the extended model of the theory of planned behavior (TPB) to understand the psychological aspects that may enhance the likelihood of university students engaging in environmentally friendly behavior.

This study used a quantitative approach involving a national sample of university student participants (N = 1,608) from various regions across Indonesia. The battery included extended TPB dimension measures (attitudes, norms, behavior control, environmental concern and habits on pro-environmental behavior intention) that were administered in the Indonesian language.

The structural equation modeling analysis revealed that the proposed extended TPB model met fit model indices and significantly predicted participants’ pro-environmental intentions.

This theoretical model has the potential to assist relevant stakeholders and higher education institutions in the development of evidence-based pro-environmental policies and interventions to promote sustainable student behavior.

This study presents a novel approach to understanding the effect of the extended TPB model on participants’ ecological intentions in the Indonesian university setting. This study was among the first to propose a sustainable behavior intention model based on the TPB theory within the Indonesian context. The current findings challenged the established TPB framework and offered fresh insights into the behavioral-psychological interplay within university environmental contexts.

This paper aims to assess the current and future dynamics of land cover transitions and analyze the vegetation conditions in Abuja city since its establishment as the capital of Nigeria in 1991.

A random forest classifier embedded in the Google Earth Engine platform was used to classify Landsat imagery for the years 1990, 2001, 2014 and 2020. A post-classification comparison was used to detect the dynamics of land cover transitions. A hybrid simulation model that comprised cellular automata and Markovian was used to model the probable scenario of land cover changes for 2050. The trend of Normalized Difference Vegetation Index was examined using Mann–Kendall and Theil Sen’s from 2014 to 2022. Nighttime band data from the National Oceanic and Atmospheric Administration were obtained to analyze the trend of urbanization from 2014 to 2022.

The findings show that built-up areas increased by 40%, while vegetation, bare land and agricultural land decreased by 27%, 7% and 8%, respectively. Vegetation had the highest declining rate at 3.15% per annum. Built-up areas are expected to increase by 17.1% between 2020 and 2050 in contrast with other land cover. The proportion of areas with moderate vegetation improvement is estimated to be 15.10%, while the proportion of areas with no significant change was 38.10%. The overall proportion of degraded areas stands at 46.8% due to urbanization.

The findings provide a comprehensive insight into the dynamics of land cover transitions and vegetation variability induced by rapid urbanization in Abuja city, Nigeria. In addition, the findings provide valuable insights for policymakers and urban planners to develop a sustainable land use policy that promotes inclusivity, safety and resilience.

Anchored in the theories of brand gestalt and stakeholder perspectives, this study aims to undertake a comprehensive examination of the brand gestalt concept, emphasizing its multidimensional nature and the process of co-creation.

Focused within the context of the Wonderful Indonesia brand, the research draws upon a rich qualitative data set derived from in-depth interviews conducted with 18 international tourists, supplemented by netnography (or internet ethnography) of websites, social media and online articles related to Wonderful Indonesia. Using grounded theory methodology, the qualitative data undergo rigorous analysis to identify emergent themes and patterns.

The research elucidates the four dimensions (4S) comprising brand gestalt: storyscapes, sensescapes, servicescapes and stakeholderscapes. Each dimension is further delineated into essential categories, providing a comprehensive understanding of brand gestalt. This study highlights the collaborative nature of brand gestalt, emphasizing the involvement of multiple stakeholders in shaping the brand's identity and perception. Consumer perceptions of co-creation are identified as significant contributors to brand gestalt, enhancing the brand's value proposition.

Destination management and practitioners can use the insights from the research to refine their brand management and marketing strategies by leveraging the dimensions of brand gestalt. Recognizing the collaborative construct of brand gestalt can guide businesses in fostering meaningful relationships with stakeholders and aligning branding efforts with collective visions. Understanding the role of consumer co-creation in brand development can inform strategies aimed at enhancing brand equity and fostering consumer loyalty.

This study extends existing literature on brand gestalt by providing a comprehensive examination of its four dimensions and essential categories. By emphasizing the collaborative nature of brand gestalt, this study contributes to advancing the understanding of brand co-creation paradigms. The identification of consumer perceptions of co-creation as a significant factor in brand gestalt adds novel insights to the literature, offering valuable implications for brand management and marketing strategies.

To achieve the Sustainable Development Goals (SDGs) in the era of Logistics 4.0, machine learning (ML) techniques and simulations have emerged as highly optimized tools. This study examines the operational dynamics of a supply chain (SC) in Vietnam as a case study utilizing an ML simulation approach.

A robust fuel consumption estimation model is constructed by leveraging multiple linear regression (MLR) and artificial neural network (ANN). Subsequently, the proposed model is seamlessly integrated into a cutting-edge SC simulation framework.

This paper provides valuable insights and actionable recommendations, empowering SC practitioners to optimize operational efficiencies and fostering an avenue for further scholarly investigations and advancements in this field.

This study introduces a novel approach assessing sustainable SC performance by utilizing both traditional regression and ML models to estimate transportation costs, which are then inputted into the discrete event simulation (DES) model.

Social value creation (SVC) is the primary emphasis for unifying the various issues in contemporary social entrepreneurship (SE) literature and practice since it highlights the fundamental problem of sustainability in SE business. Accordingly, SVC as an outcome of SE represents the primary drive of social entrepreneurs (SEs). However, SEs encounter multi-dimensional challenges as they work to build their SE businesses and create social value. In the current context of digitally transforming entrepreneurship scenario, this study investigates the role of SE compassion and digital learning orientation (DLO) for SVC ability of SEs.

The study utilized a quantitative survey approach for primary data collection from social entrepreneurs in Saudi Arabia. A total of 158 valid replies from social entrepreneurs were obtained for the study. Using SmartPLS (3.0), partial least square structural equation modeling was used to analyze the data.

The results validated a model of SVC in which the SE compassion and DLO positively impact the SVC ability in SEs. However, the impact of DLO in moderating the SE compassion - SVC relationship in SEs was not proven.

The study established the role of SE compassion in explaining the distinctive SVC ability in SEs. Meanwhile, given the expanding necessity for SEs to leverage digital technologies for SE missions, the study provides implications for nurturing positive outcomes in terms of SE compassion and DLO outcomes among SEs. This organized knowledge can help entrepreneurs, educators and policymakers better incorporate these concerns in SE education, and social enterprises and entrepreneurs’ developmental initiatives.

This work is pioneering in that it conceptualizes and tests a theoretical framework that links SE compassion, DLO, and SVC in SEs. Meanwhile, the study is the first to operationalize the DLO in entrepreneurs. The study thus generates fresh insights about SVC in SE amid the digitally transforming entrepreneurship scenario.

Public procurement presents substantial market opportunities for small- and medium-sized enterprises (SMEs), which can contribute to their economic growth. However, limited dynamic capabilities often pose challenges for SMEs to participate effectively in public procurement markets. Drawing on dynamic capability (DC) theory, this study explores whether financial capability (FNCP) influences SMEs’ ability to leverage their technological capability (TECC) and marketing sensing capability (MKSC) and actively engage in public procurement.

Data for this study were collected from 248 SME managers in the Ilala District, Tanzania, using a cross-sectional questionnaire survey and stratified random sampling technique. The proposed hypotheses were tested empirically through confirmatory factor analysis (CFA) and the Hayes PROCESS macro.

TECC and MKSC demonstrated significant positive associations with SME participation in public procurement (SMPP). Moreover, the interaction between TECC and FNCP as well as the interaction between MKSC and FNCP demonstrate a significant positive effect, suggesting that FNCP strengthens the impact of TECC and MKSC on SMPP.

The scope of this study was limited to SMEs in the Ilala District of Tanzania, hence affecting the generalizability of the findings to other contexts. More importantly, the study findings enrich the understanding of DC theory, signifying that the integration and reconfiguration of MKSC, TECC and FNCP add significant value to SMPP.

The findings suggest that policymakers, support institutions and SME managers should focus on enhancing SMEs' MKSC and TECC to improve their participation in public procurement. In addition, improving SMEs' access to financial resources can further strengthen these effects, enabling more inclusive participation in public procurement.

The study contributes to the literature on SMPP by highlighting the critical roles of MKSC and TECC. It also underscores the importance of FNCP as a moderator in these relationships, which has not been addressed in the existing literature. By integrating these factors, the study offers a comprehensive framework for understanding the dynamics that influence SMPP from financial, technological and marketing perspectives, particularly in developing economies like Tanzania.

Previous studies have postulated that an advance payment system (APS) positively impacts the contractor's working capital and is paramount to ensuring an efficient and effective project cash flow process. However, scant research has been undertaken to empirically establish the cash flow performance and domino effect of APS on project and organisational performance.

The epistemological design adopted a positivist philosophical stance augmented by deductive reasoning to explore the phenomena under investigation. Primary quantitative data were collected from 504 Construction Industry Development Board (CIDB) registered contractors (within the grade bandings 1–9) in South Africa. A five-point Likert scale was utilised, and subsequent data accrued were analysed using structural equation modelling (SEM).

Emergent findings reveal that the mandatory use of an APS does not guarantee a positive project cash flow, an improvement in organisational performance or an improvement in project performance.

The ensuing discussion reveals the contributory influence of APS on positive cash flow and organisational performance, although APS implementation alone will not achieve these objectives. Practically, the research accentuates the need for various measures to be concurrently adopted (including APS) towards ensuring a positive project cash flow and improved organisational and project performance.

There is limited empirical research on cash flow performance and the domino effect of APS on project and organisational performance in South Africa, nor indeed, the wider geographical location of Africa as a continent. This study addresses this gap in the prevailing body of knowledge.