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Linear projects often involve lengthy construction periods, necessitating dynamic adjustments to the plan. Completely rescheduling remaining activities every time can lead to unnecessary time and cost wastage and significant deviations in resource supply. To address these issues, this paper proposes a dynamic scheduling method designed to effectively manage both time and cost during construction projects.

Determining the rescheduling frequency through a hybrid driving strategy and buffer mechanism, introducing rolling window technology to determine the scope of local rescheduling and constructing a local rescheduling model under the constraints of time and cost deviation with the objective of minimizing the cost. Combined decision-making for construction and rushing modes constrained by multiple construction scenarios. Opposite learning is introduced to optimize the hybrid algorithm solution.

Arithmetic examples and cases confirm the model’s feasibility and applicability. The results indicate that (1) continuous rescheduling throughout project construction is essential and effective and (2) a well-structured buffer mechanism can prevent redundant rescheduling and enhance overall control of cost and schedule deviations.

This study introduces an innovative dynamic scheduling framework for linear engineering, offering a method for effectively controlling schedule deviations during construction. The developed model enhances rescheduling efficiency and introduces a combined quantization strategy to increase the model’s applicability to linear engineering. This model emerges as a promising decision support tool, facilitating the implementation of sustainable construction scheduling practices.

Mobile banking (or m-banking) has become an inseparable part of the modern finance model. Its success relies on customers’ affective responses and behavioral decisions. This study aims to examine the important determinants of positive word-of-mouth (POW) toward m-banking among older consumers.

A quantitative approach was applied in examining a proposed model with data obtained from 358 respondents based on a Web-based survey from Vietnam using a questionnaire.

It was determined that attitude, usage intention and satisfaction are the fundamental facilitators of POW in m-banking. Furthermore, perceived usefulness, ease of use and trust are the main predictors of attitude and usage intention, and epistemic value, conditional value, social value and technological value are the primary motivators of usage intention. Ease of use and trust positively affect perceived usefulness. Usage intention fosters higher levels of satisfaction. This study affirms the insignificant effects of ease of use and hedonic value on usage intention as well as satisfaction on attitude.

The findings are insightful for developers to concentrate on how to promote cognitive, affective and behavioral responses among old consumers in m-banking. Marketers should boost value perceptions and trust as the prerequisite underlying judgment and behaviors toward m-banking.

This work validates the synergistic model of POW among older consumers in m-banking by combining the technology acceptance model (TAM) and theory of consumption values (TCV). Thus, it would increase the exploratory power of the theoretical base toward m-banking and in an emerging market.

Given the widespread adoption of empowerment in the workplace, increasing research has investigated the influences of empowering leadership. However, previous research has found confounding effects of it. This study aims to examine how and when empowering leadership exhibits “double-edged sword” effects on followers’ work outcomes.

The authors used a three-wave survey with a final sample of 215 full-time employees to test the research model.

The results indicate that followers’ role-breadth self-efficacy (RBSE) interacted with empowering leadership to predict their hindrance-related stress, subsequently influencing their turnover intention. Specifically, empowering leadership is found to elicit hindrance-related stress among followers with low RBSE. Furthermore, empowering leadership indirectly affects turnover intention by eliciting hindrance-related stress only among followers with low RBSE.

This study broadens the exploration of the “dark side” of empowering leadership, offering a more nuanced explanation of how it can lead to both beneficial and detrimental outcomes. It refines the understanding of empowering leadership’s effectiveness by highlighting the role of followers’ RBSE rather than focusing solely on the degree of empowerment. In addition, by contributing to the stress theory, this research demonstrates how individual differences influence followers’ cognitive appraisal of stress, shaping distinct stress experiences and driving the adoption of varying work-related coping strategies.

This study aims to gain a better understanding of artificial serendipity – pre-planned surprises intentionally crafted through deliberate designs – in online marketplaces. By exploring the key features of artificial serendipity, this study investigates whether serendipity can be intentionally designed, particularly with the use of artificial intelligence (AI). The findings from this research broaden the scope of serendipity studies, making them more relevant and applicable in the context of the AI era.

A narrative study was conducted, gathering insights from 32 Chinese online consumers through diaries and interviews. The data were analysed in close collaboration with participants, ensuring an authentic reflection of their perceptions regarding the features of artificial serendipity in online marketplaces.

Findings reveal that artificial serendipity, particularly when designed by AI, is still regarded by online consumers as genuine serendipity. It provides a sense of real surprise and encourages deeper reflection on personal knowledge, affording the two central qualities of genuine serendipity: unexpectedness and valuableness. However, since artificial serendipity is pre-planned through intentional design, consumers cannot have entire control over it. Therefore, compared to natural serendipity – fortune surprises arising from accidental correspondence between individuals and contexts – artificial serendipity tends to be more surprising yet less valuable.

For research, it highlights the potential of intelligent technologies to facilitate genuine serendipity, updating our understanding of serendipity.

Also, the study provides practical insights into designing serendipity, especially in online markets. These contributions enrich both the theoretical framework and practical strategies surrounding serendipity in the era of AI.

This study stands out as one of the few to provide a nuanced understanding of artificial serendipity, offering valuable insights for both research and practice. For research, it highlights the potential of intelligent technologies to facilitate genuine serendipity, updating our understanding of serendipity. Also, the study provides practical insights into designing serendipity, especially in online markets. These contributions enrich both the theoretical framework and practical strategies surrounding serendipity in the era of AI.

This study aims to explore the factors influencing the evolution of emerging technology innovation network (ETIN) in combination with the key attributes and life cycle of emerging technologies, particularly the impact of multiple knowledge attributes and technology life cycle on the ETIN evolution.

This study collects 5G patent data and their citation information from the Derwent Innovations Index to construct a 5G technology innovation network (5GIN) as a sample network and conducts an empirical analysis of the 5GIN using the temporal exponential random graph model (TERGM).

The results indicate that during the 5GIN evolution, the network scale continues to expand and exhibits increasingly significant core-periphery structure, scale-free characteristic, small-world characteristic and community structure. Furthermore, the findings suggest that the multiple knowledge attributes based on the key attributes of emerging technologies, including knowledge novelty, coherence, growth and impact, have a significant positive influence on the ETIN evolution. Meanwhile, the temporal evolution of ETIN is also found to be correlated with the life cycle of emerging technologies.

This study extends the exploration of emerging technology research from a complex network perspective, providing a more realistic explanatory framework for the factors influencing ETIN evolution. It further highlights the important role that multiple knowledge attributes and the technology life cycle play within this framework.

This work intends to evaluate experimentally the ratcheting behaviour of AM MS300. Furthermore, cyclic plasticity modelling (modified Abdel-Karim and Ohno model) is examined as a means of predicting ratcheting.

Uniaxial stress-controlled cyclic loading histories were utilised to evaluate ratcheting for Maraging Steel 300 (MS300) fabricated via laser powder bed fusion (LPBF) additive manufacturing (AM). Heat-treated and as-built AM and conventionally manufactured (CM) MS300 coupons were tested at room temperature, under constant and incrementally variable stress amplitude and mean stress. Two sets of AM test coupons were used, printed at horizontal and vertical built orientation. The AM material ratcheting was predicted via constitutive modelling and numerical simulation. The Abdel-Karim and Ohno cyclic plasticity model was modified by introducing a memory surface, to improve ratcheting prediction.

The hysteresis stress–strain response and low cycle fatigue (LCF) life were obtained from the different loading histories. Both the AM and CM MS300 exhibited an accumulation of axial strain (ratcheting) for all tests, attributed to the application of non-zero mean stress. The AM MS300 has demonstrated a higher ratcheting accumulation rate than the CM material. The achieved agreement between the numerical results of the new model and the experimental data offers an indication on the suitability and the robustness of this model.

The ratcheting behaviour of the AM MS300 material has been characterised for the first time in the published literature, for a variety of loading histories selected. A modified Abdel-Karim and Ohno plasticity model has been developed to account for the ratcheting performance of this material.

Prosperity is a multifaceted concept that encompasses human well-being through economic and non-economic aspects, as well as material and immaterial attributes. Prosperous development refers to a community’s ability to thrive physically, socially, and psychologically while integrating environmental priorities and social objectives with economic directions. The City Prosperity Initiative (CPI) conceptualizes the broad understanding of human and societal livability and well-being regarding sustainable and inclusive urban development. Hence, this paper aims to elucidate urban prosperity and explore it in Tehran using the CPI Index.

It was possible to analyze Tehran’s prosperous development by valuing 56 indicators of the CPI Index, which served as a composite indicator based on reliable secondary data from official statistical yearbooks and reports. Instead of employing a global weighting methodology for aggregating sub-dimensions and dimensions, the analysis considered local context and priorities, incorporating insights from experts and scholars. For this purpose, the CPI’s methodology and metadata and the Analytical Hierarchy Process (AHP) logic were applied using Expert Choice software.

Tehran’s overall prosperity score is 47.6 out of 100, indicating a weak and vulnerable status. The asymmetric hexagonal shape of Tehran’s CPI Index reflects the unbalanced development of its urban system. Quality of Life and Infrastructure Development are solid, while Equity and Social Inclusion is fragile. Productivity, Environmental Sustainability and Urban Governance and Legislation are very weak. Thus, environmental unsustainability, low productivity, and inadequate governance and legislation significantly hinder Tehran’s prosperous development. Unsatisfactory conditions of social infrastructure and economic equity exacerbate this problematic situation.

As one of the largest metropolises in the Middle East and one of the globalizing cities from developing countries and emerging economies, Tehran has not yet been studied using the CPI. This study adds Tehran to the limited number of cities analyzed through the CPI. Tehran has surpassed its carrying capacity, and if current trends continue, its quality of life will also be fragile. The city’s environmental challenges are evident, and experts and scholars are well aware of these issues and concerned about the situation.

Despite the difficulty of obtaining accurate and reliable data and the need for a robust weighting system, the CPI framework remains adaptable. It allows for modifications based on the study’s objectives, scale, and context. In addition to the strategies proposed to improve Tehran’s prosperity, enhancing urban prosperity could be expected only through adopting an integrated approach that addresses all dimensions regarding environmental priorities, social objectives, and economic directions, considering the unique needs and preferences of the city at local, regional, national, and transnational planning levels.

This paper aims to explore sociocultural factors as determinants of entrepreneurial emergence and to examine their relative influence (i.e. the influence of each factor) on entrepreneurial emergence.

A survey design with a questionnaire instrument administered to 250 business owners selected randomly from a cross section of businesses was used. The data were analyzed using the descriptive method, pairwise comparison, Kendall’s W test and Mean Rank Statistics.

This study showed that the level of influence of sociocultural factors on the decision to own a business by an individual in Africa varies by factor. Family background is the factor that has the highest influence, whereas religious values has the least influence. Altogether, nine most significant factors influence the choice of business ownership in Nigeria and in Africa generally. These include family background, unemployment, family values, inadequate income, job displacement, stock of social capital, role models, social networks and lack of social security, in that order.

Although some scholars may have explored sociocultural factors as determinants of entrepreneurial emergence, there is no study on their relative influence on entrepreneurial emergence, at least not in the context of Africa or Nigeria in particular. This study extends previous studies by examining the relative influence of the factors, using Nigeria as a reference for Africa. A focus on their relative influence is a new perspective on the study of sociocultural factors as determinants of entrepreneurial emergence.

Tacit knowledge in frontline operations is primarily reflected in the holders’ intuition about dynamic systems. Despite the implicit nature of tacit knowledge, the understanding of complex systems it encapsulates can be displayed through formalization methods. This study seeks to develop a methodology for formalizing tacit knowledge in a dynamic delivery system.

This study employs a structured survey to gather experiential knowledge from dispatchers engaged in last-mile delivery operations. This knowledge is then formalized using a value function approximation approach, which transforms tacit insights into structured inputs for dynamic decision-making. We apply this methodology to optimize delivery operations in an online-to-offline pharmacy context.

The raw system feature data are not strongly correlated with the system’s development trends, making them ineffective for guiding dynamic decision-making. However, the system features obtained through preprocessing the raw data increase the predictiveness of dynamic decisions and improve the overall effectiveness of decision-making in delivery operations.

This research provides a foundational framework for studying sequential dynamic decision problems, highlighting the potential for improved decision quality and system optimization through the formalization and integration of tacit knowledge.

This approach proposed in this study offers a method to preserve and formalize critical operational expertise. By embedding tacit knowledge into decision-making systems, organizations can enhance real-time responsiveness and reduce operational costs.

This study presents a novel approach to integrating tacit knowledge into dynamic decision-making frameworks, demonstrated in a real-world last-mile delivery context. Unlike previous research that focuses primarily on explicit data-driven methods, our approach leverages the implicit, experience-based insights of operational staff, leading to more informed and effective decision-making strategies.

The purpose of this study is to identify the determinants of success in peer-to-peer (P2P) lending campaigns, especially amid global financial disruptions like the COVID-19 pandemic. Addressing a notable gap in current research, we explore how factors such as firm uncertainty, loan characteristics (interest rates and maturity) and venture quality (human, social and intellectual capital) influence P2P lending effectiveness. Using multiple regression analysis on data from 523 projects on the October platform, our study aims to enhance the understanding and operational efficiency of P2P platforms, contributing to a more resilient financial ecosystem.

This study employs a quantitative research design using multiple regression analysis to examine the impact of specific variables on the success of P2P lending campaigns. Data were collected from 523 concluded P2P lending projects on the October platform, spanning from 2015 to 2021. Variables of interest include the level of uncertainty of the firm, loan characteristics such as interest rate and maturity and the quality of the venture assessed through human, social and intellectual capital. This method allows for a robust analysis of the factors contributing to the success of P2P lending within a dynamic financial context.

The findings of this study reveal that the success of P2P lending campaigns is significantly influenced by the level of uncertainty of the firm, the interest rate of the loan and the quality of the venture. Specifically, higher uncertainty in firms correlates negatively with campaign success, while competitive interest rates positively impact funding outcomes. Furthermore, ventures that demonstrate robust human capital, particularly those with management teams that possess diverse skills and high qualifications, tend to attract more funding. These results underscore the critical role of strategic financial and human resource planning in enhancing the effectiveness of P2P lending platforms.

This study contributes uniquely to the literature by integrating multiple variables – firm uncertainty, loan characteristics and venture quality – into a comprehensive analysis of success factors in P2P lending. It addresses the scarcity of research examining the combined effects of these factors, particularly in the context of global financial disruptions like the COVID-19 pandemic. By focusing on a specific European platform during a dynamic period, this research provides new insights into how P2P lending can adapt to and thrive amid financial crises. The findings offer valuable guidance for both practitioners and policymakers aiming to optimize P2P lending practices in uncertain economic landscapes.