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Prefabricated building has been widely applied in the construction industry all over the world, which can significantly reduce labor consumption and improve construction efficiency compared with conventional approaches. During the construction of prefabricated buildings, the overall efficiency largely depends on the lifting sequence and path of each prefabricated component. To improve the efficiency and safety of the lifting process, this study proposes a framework for automatically optimizing the lifting path of prefabricated building components using building information modeling (BIM), improved 3D-A* and a physic-informed genetic algorithm (GA).

Firstly, the industry foundation class (IFC) schema for prefabricated buildings is established to enrich the semantic information of BIM. After extracting corresponding component attributes from BIM, the models of typical prefabricated components and their slings are simplified. Further, the slings and elements’ rotations are considered to build a safety bounding box. Secondly, an efficient 3D-A* is proposed for element path planning by integrating both safety factors and variable step size. Finally, an efficient GA is designed to obtain the optimal lifting sequence that satisfies physical constraints.

The proposed optimization framework is validated in a physics engine with a pilot project, which enables better understanding. The results show that the framework can intuitively and automatically generate the optimal lifting path for each type of prefabricated building component. Compared with traditional algorithms, the improved path planning algorithm significantly reduces the number of nodes computed by 91.48%, resulting in a notable decrease in search time by 75.68%.

In this study, a prefabricated component path planning framework based on the improved A* algorithm and GA is proposed for the first time. In addition, this study proposes a safety-bounding box that considers the effects of torsion and slinging of components during lifting. The semantic information of IFC for component lifting is enriched by taking into account lifting data such as binding positions, lifting methods, lifting angles and lifting offsets.

This paper aims to investigate the interrelated role of relational commitment and dependence as drivers of key performance outcomes. Specifically, the authors provide a conceptual model of the impact of commitment on relationship value dependence and switching cost dependence. The authors further investigate how these dimensions of dependence offer differing noneconomic and economic paths to strategic and financial performance.

Survey data was collected from 296 purchasing agents across multiple industries located in the USA. The conceptual model and accompanying hypotheses were tested via partial least squares structural equation modeling.

The results show that the relational path is driven by affective and normative commitment, which are related to relationship value dependence. Conversely, calculative commitment is related to switching cost dependence. This economic path is related to both strategic and financial performance, whereas the relational path is more closely related to strategic as opposed to financial performance outcomes.

This study extends research on Business-To-Business (B2B) relationships by leveraging social exchange theory to examine the interrelated roles played by two forms of dependence on performance outcomes. Thus, the authors answer Scheer et al.’s (2015) call for research into the two distinct types of dependence – relationship value and switching cost dependence – and their roles in determining B2B relationship outcomes. The findings contribute to the literature by integrating social exchange and relationship marketing concepts to develop a dual pathway approach to B2B partnerships.

The results suggest that dependence is not necessarily negative for firms. Specifically, buyers can and do still exhibit positive performance, both strategic and financial, in relationships with suppliers even when dependent on the relationship. Regardless of whether buyers are dependent due to a relationship or economic factors, both can, in different ways, lead to positive strategic and financial outcomes. Together, the authors contribute to the understanding of B2B partnerships by offering guidelines for both buyers and suppliers in the dyad.

The authors derive a comprehensive model depicting primarily relational and economic paths to performance through different types of commitment and dependence. The authors contribute to the literature by demonstrating that relational and economic paths to success are not the same, highlighting how firms could influence performance even when the relationship is not necessarily characterized by generally positive relational benefits and behaviors.

Researchers explore the impact of an intelligent assistant in virtual teams by applying the theoretical lens of a transactive memory system (TMS) to understand the relationships between trust in a specific technology, knowledge sharing and knowledge application.

An online survey was administered to a Qualtrics-curated panel of individual, US-based virtual team members utilizing an intelligent assistant with team collaboration software. Partial least squares structural equation modeling (PLS-SEM) was utilized to examine the hypothesized relationships of interest.

Results suggest that knowledge application is strongly influenced by trust in a specific technology and knowledge sharing. Additionally, a transactive memory system positively increases trust in the intelligent assistant, and similarly, trust in the intelligent assistant has a significant positive relationship with knowledge sharing.

The research model contributes to our understanding of the impact of an intelligent assistant in virtual teams. Although the transactive memory system construct has been explored in various contexts and models, few have explored the impact of an intelligent assistant and trust in a specific technology.

This study investigated the concerns and plans of construction professionals about building information modeling (BIM) implementation, found the acceptable BIM implementation driving forces and strategies for them and developed a prescriptive BIM implementation model to help understand how BIM implementation concerns, intentions, driving forces and strategies are connected.

This study employs a positivist paradigm with a hypothetico-deductive research strategy as well as concern-based adoption theory as a conceptual lens to distinguish construction professionals (CPs)' BIM implementation concerns and intentions. This implies that the forces driving BIM implementation intentions and concerns are related to BIM implementation methods and that their concentrations are proportional to the intensity of BIM implementation strategies. A 16-item questionnaire tailored to the operations of CPs was used for data collection. The data collected from respondents were utilized to evaluate the proposed model using structural equation modeling (SEM) techniques.

Findings from the data collected from the respondents revealed that CPs are concerned about the impact of BIM deployment on their time and service quality. Their main purpose was to take drives to learn more about BIM in order to pique their curiosity. Embracing the latest digital technology and beginning self-initiated BIM training are two strategies that would be quite effective in boosting BIM deployment.

The study identifies promising directions for future BIM implementation research and development. The study's findings imply that more theoretically motivated research, rather than just empirical research, is required to refine BIM implementation concerns.

The study has implications for the professional development of CPs as well as understanding the process of implementing BIM change. The study's findings will help to understand the resource system for assessing CPs' needs and concerns and selecting personalized BIM implementation strategies.

Before this study, BIM-related studies had ignored the concerns and goals of the CPs when it came to implementing BIM. Using the CPs' concerns and hopes for BIM implementation, a systemic BIM implementation model was developed that would help and speed up BIM adoption.

This study aims to investigate how social entrepreneurial role models influence social entrepreneurial self-efficacy, social entrepreneurial intent and social entrepreneurial action, with moral obligation as a moderator.

A cross-sectional survey of 261 pupils in the South African province of the Eastern Cape was used in the research study. Structural equation modeling was used to test hypotheses.

The research revealed that having social entrepreneurial role models has a positive impact on both social entrepreneurial self-efficacy and social entrepreneurial intent. In addition, a connection was found between social entrepreneurial intent and entrepreneurial action. The influence of moral obligation was found to be a positive and a significant moderator. Moreover, the association between social entrepreneurial role models and social entrepreneurial intent was mediated by social entrepreneurial self-efficacy.

The findings are not generalizable to nonstudent samples because students constituted the sample for gathering data. Future study therefore requires considering nonstudents to generalize the outcomes. This research should be replicated in other South African provinces and other developing countries for comparative outcomes.

Since social entrepreneurial role models have been practically linked to social entrepreneurship intent and entrepreneurial efficacy, understanding the factors that influence student’s decision to start a social enterprise is critical in South Africa to develop targeted interventions aimed at encouraging young people to start new businesses. Policymakers, society and entrepreneurial education will all benefit from the findings.

This study contributes to bridging the knowledge gap as it investigates how social entrepreneurial role models influence social entrepreneurial self-efficacy, social entrepreneurial intent and social entrepreneurial action, with moral obligation as a moderator. Encouraging social entrepreneurship among South African youth would also help address societal issues. This is a pioneering study in the context of an emerging economy such as South Africa, where social entrepreneurship is so integral.

Despite the considerable increase in research on entrepreneurship education, few studies examine the role of entrepreneurship educators. Similarly, most frameworks from entrepreneurship education recognize the educator’s importance in facilitating instruction and assessment, but the factors influencing the educator role are not well understood. According to the identity theory, personal factors including self-efficacy, job satisfaction and personal values influence the perspective of self, significance and anticipations that an individual in this role associates with it, determining their planning and actions. The stronger the role identity the more likely entrepreneurship educators will be in effectively developing their entrepreneurial skills as well as the overall learning experience of their students. The objective of this study is to pinpoint the factors that affect entrepreneurial role identity.

Drawing upon the identity theory, this study developed a theoretical framework and carried out an empirical investigation involving a survey of 289 entrepreneurship educators across the globe. Structural equation modeling (SEM) technique was applied to analyze and explore the factors that impact the identity of the educators in their role as entrepreneurship teachers.

The findings show that the role identity of entrepreneurship educators is significantly influenced by their self-efficacy, job satisfaction and personal values. Among these factors, self-efficacy and job satisfaction have the most significant impacts on how educators perceive their role. The implications of these results and directions for future research are also discussed.

The novelty of the current study is derived from its conceptualization of the antecedents of role perception among entrepreneurship educators. This study stands out as one of the earliest attempts to investigate the factors that shape an individual’s scene of self and professional identity as an entrepreneurship educator. The significance of comprehending the antecedents of role perception lies in the insights it can offer into how educators undertake and execute their role, and consequently, their effectiveness in teaching entrepreneurship.

The purpose of this paper is to investigate how different manufacturing technologies are bundled together and how these bundles influence operations performance and, indirectly, business performance. With the emergence of Industry 4.0 (I4.0) technologies, manufacturing companies can use a wide variety of advanced manufacturing technologies (AMT) to build an efficient and effective production system. Nevertheless, the literature offers little guidance on how these technologies, including novel I4.0 technologies, should be combined in practice and how these combinations might have a different impact on performance.

Using a survey study of 165 manufacturing plants from 11 different countries, we use factor analysis to empirically derive three distinct manufacturing technology bundles and structural equation modeling to quantify their relationship with operations and business performance.

Our findings support an evolutionary rather than a revolutionary perspective. I4.0 technologies build on traditional manufacturing technologies and do not constitute a separate direction that would point towards a fundamental digital transformation of companies within our sample. Performance effects are rather weak: out of the three technology bundles identified, only “automation and robotization” have a positive influence on cost efficiency, while “base technologies” and “data-enabled technologies” do not offer a competitive advantage, neither in terms of cost nor in terms of differentiation. Furthermore, while the business performance impact is positive, it is quite weak, suggesting that financial returns on technology investments might require longer time periods.

Relying on a complementarity approach, our research offers a novel perspective on technology implementation in the I4.0 era by investigating novel and traditional manufacturing technologies together.

This study analyzes, from the perspective of social exchange theory, the influence of empowering leadership on contextual performance mediated by perceived organizational support (POS) and affective organizational commitment (AOC).

A survey was carried out with 182 employees of the Best Companies to Work in Brazil. Data analysis was performed by structural equation modeling (SEM) and by fuzzy set qualitative comparative analysis (fsQCA).

Results demonstrate that empowering leadership directly influences higher contextual performance and indirectly through the mediation of AOC, but not through POS. Serial mediation confirms that the model's variables self-promote each other to ultimately foster higher performance. Furthermore, all solutions to obtain high contextual performance include empowering leadership in the dimension of trust in the high performance of employees.

The statistical support for the serial mediation indicates that empowering leadership promotes POS, which influences AOC that finally promotes the employee's contextual performance. However, this study's model does not include employees' task performance; our results add to the contextual performance literature.

The study highlights the role of the empowering leadership style in the organizational context, an aspect that deserves attention from the managers and organizations due to its effect on employee performance.

The study adds a new framework to the literature, which can be used by organizations to promote contextual performance. The variables, which include contextual and individual factors, foster the employee's contextual performance in a joint and self-promoting way. Contextual performance exceeds the manager's technical attributions; it covers psychological and discretionary behaviors.

Within the umbrella of technology and vocational education (TVET), technology or technical education in higher institutions of learning is obligated to produce the required manpower needed in the industry. Thus, it is pertinent to explore the interaction between the industry and higher education students. Drawing on the tenets of theory of planned behavior (TPB), this study offers valuable insights into the nomological networks of work-integrated learning (WIL), perceived behavioral control (PBC), subjective norm (SBN), personal attitude (PAT) and job search intention (JSI).

The study applied a structurally hypothesized model that was drawn from the TPB to collect data for the constructs. Using a cross-sectional survey after the WIL experiences of the students, we collected data from technology education undergraduates (N = 214) in their final academic year from universities in Nigeria.

With structural equation modeling, the study found that WIL is directly associated with JSI, PBC, SBN and PAT. In line with the tenets of the TPB, simple mediation models were supported about the influence of WIL on JSI via PBC and PAT discretely but not via SBN. Further, the results support two paths of serial mediation models, indicating sequential indirect links between WIL and JSI via SBN and PBC, as well as via SBN and PAT.

Our findings have implications for higher education practitioners, industry experts and employers of labor.

Although extant literature has relatively shown that WIL impacts employability skills, this study has remarkably shown the WIL-JSI nexuses within the variables of TPB.

This study aims to empirically examine accounting information system (AIS) success at the organizational level during COVID-19 era.

Based on the information system success model, this paper developed its model and proposed a total of nine hypotheses. This paper gathered the required data via a questionnaire from Yemeni small and medium enterprises (SMEs) owners and managers. To test the proposed research model paths, SmartPLS software, which is known as partial least squares structural equation modeling, was used.

The results showed that the quality dimensions (information quality and system quality) positively affected the use of AIS and satisfaction; user satisfaction positively affected the use of AIS. Management support positively affected the AIS users' usage and satisfaction. Finally, the use dimensions (user satisfaction and usage) positively impacted the net benefits in terms of gaining a competitive advantage, productivity enhancement and saving time and cost. In all, this research has succeeded in providing support for DeLone and McLean's IS success model at the organizational level during the COVID-19 era.

AIS is becoming increasingly important for SMEs in low-income countries like Yemen, particularly in the present pandemic conditions (COVID-19 era). By using AIS, users can access the enterprise's data and conduct transactions without being limited by distance. Indeed, AIS proved its ability in enhancing the net benefits at the organizational level in the COVID-19 era in terms of gaining a competitive advantage, productivity enhancement and saving time and cost. However, AIS can only be considered useful to the enterprise if it is effective/successful.

This study is one of the first to have assessed the impact of AIS success at the organizational level in the era of COVID-19 pandemic, the context of Yemeni SMEs.