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This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase, construction companies must assess the scope of each task and map the client’s expectations to an internal database of tasks, resources and costs. Quantity surveyors carry out this assessment manually with little to no computer aid, within very austere time constraints, even though these results determine the company’s bid quality and are contractually binding.

This paper seeks to compile applications of machine learning (ML) and natural language processing in the architectural engineering and construction sector to find which methodologies can assist this assessment. The paper carries out a systematic literature review, following the preferred reporting items for systematic reviews and meta-analyses guidelines, to survey the main scientific contributions within the topic of text classification (TC) for budgeting in construction.

This work concludes that it is necessary to develop data sets that represent the variety of tasks in construction, achieve higher accuracy algorithms, widen the scope of their application and reduce the need for expert validation of the results. Although full automation is not within reach in the short term, TC algorithms can provide helpful support tools.

Given the increasing interest in ML for construction and recent developments, the findings disclosed in this paper contribute to the body of knowledge, provide a more automated perspective on budgeting in construction and break ground for further implementation of text-based ML in budgeting for construction.

When is it more profitable for multinational manufacturers to manufacture in high-cost environments and when in low-cost environments? While the literature offers many cues to answer this question, too little empirical research directly addresses this. In this study, we quantitatively and empirically investigate the financial effect of companies' production footprint in low-cost and high-cost environments for different types of production networks.

Using the data of 770 multinational manufacturing companies, we analyze the relationship between production footprints and profitability during four calendar semesters in 2018 and 2019 (N = 2,940), investigating the moderating role of companies' production network type.

We find that companies with networks distinguished by both high levels of product complexity and process sophistication profit the most from producing to a greater extent in high-cost countries. For these companies, shifting production to low-cost countries would be associated with negative performance implications.

Our findings suggest that the production geography of companies should be attuned to their network type, as defined by the companies' process sophistication and product complexity. Manufacturing in low-cost countries is not always the best choice, as doing so can adversely affect profits if the products are highly innovative and the production processes are complex.

We contribute to the scarce empirical literature on managing global production networks and provide a data-driven analysis that contributes to answering some of the enduring questions in this critical area.

Developing a reliable cost estimate at the early stage of construction projects is challenging due to inadequate project information. Most of the information during this stage is qualitative, posing additional challenges to achieving accurate cost estimates. Additionally, there is a lack of tools that use qualitative project information and forecast the budgets required for project completion. This research, therefore, aims to develop a model for setting project budgets (excluding land) during the pre-conceptual stage of residential buildings, where project information is mainly qualitative.

Due to the qualitative nature of project information at the pre-conception stage, a natural language processing model, DistilBERT (Distilled Bidirectional Encoder Representations from Transformers), was trained to predict the cost range of residential buildings at the pre-conception stage. The training and evaluation data included 63,899 building permit activity records (2021–2022) from the Victorian State Building Authority, Australia. The input data comprised the project description of each record, which included project location and basic material types (floor, frame, roofing, and external wall).

This research designed a novel tool for predicting the project budget based on preliminary project information. The model achieved 79% accuracy in classifying residential buildings into three cost_classes ($100,000-$300,000, $300,000-$500,000, $500,000-$1,200,000) and F1-scores of 0.85, 0.73, and 0.74, respectively. Additionally, the results show that the model learnt the contextual relationship between qualitative data like project location and cost.

The current model was developed using data from Victoria state in Australia; hence, it would not return relevant outcomes for other contexts. However, future studies can adopt the methods to develop similar models for their context.

This research is the first to leverage a deep learning model, DistilBERT, for cost estimation at the pre-conception stage using basic project information like location and material types. Therefore, the model would contribute to overcoming data limitations for cost estimation at the pre-conception stage. Residential building stakeholders, like clients, designers, and estimators, can use the model to forecast the project budget at the pre-conception stage to facilitate decision-making.

With the increasing concern over environmental pollution and global warming, companies are required to act responsibly to mitigate these environmental issues. Their activities should adhere to the standards of environmental sustainability. Thus, this study aimed to investigate the impact of green supply chain management (GSCM) and total quality management (TQM) on environmental sustainability, with environmental management practices (EMP) as the moderating factor.

A quantitative study was adopted using the management data from various manufacturing companies in Jordan. A total of 362 responses were collected, and the proposed hypotheses were tested using a structural equation model.

The study findings revealed that both GSCM and TQM significantly and positively influenced environmental sustainability. The impact of TQM on environmental sustainability was higher than that of GSCM. Moreover, no evidence was found on the moderating role of EMP.

The study’s results highlighted to the decision-makers the main practices to expand the quality implementation across their supply chain to improve environmental sustainability. The study also demonstrated the reasons behind the insignificance of EMPs in strengthening the relationships between GSCM, TQM, and environmental sustainability.

While there are very few studies examining the relationships between GSCM and TQM on environmental sustainability. This study adds to the literature body as one of a few empirical studies that tested the integrated effect of GSCM and TQM practices within the context of the manufacturing industry in a developing country. Moreover, this study takes a holistic approach by tapping into EMP to confirm whether it moderated the relationships between GSCM, TQM, and environmental sustainability.

Websites, search engines, recommender systems, artificial intelligence and digital libraries have the potential to support serendipity for unexpected interaction with information and ideas which would lead to favored information discoveries. This paper aims to explore the current state of research into serendipity particularly related to information encountering.

This study provides bibliometric review of 166 studies on serendipity extracted from the Web of Science. Two bibliometric analysis tools HisCite and RStudio (Biblioshiny) are used on 30 years of data. Citation counts and bibliographic records of the papers are assessed using HisCite. Moreover, visualization of prominent sources, countries, keywords and the collaborative networks of authors and institutions are assessed using RStudio (Biblioshiny) software. A total of 166 papers on serendipity were found from the period 1989 to 2022, and the most influential authors, articles, journals, institutions and countries among these were determined.

The highest numbers of 11 papers were published in the year 2019. Makri and Erdelez are the most influential authors for contributing studies on serendipity. “Journal of Documentation” is the top-ranking journal. University College London is the prominent affiliation contributing highest number of studies on serendipity. The UK and the USA are the prominent nations contributing highest number of research. Authorship pattern for research on serendipity reveals involvement of single author in majority of the studies. OA Green model is the most preferred model for archiving of research articles by the authors who worked on serendipity. In addition, majority of the research outputs have received a citation ranging from 0 to 50.

To the best of the authors’ knowledge, this paper may be the first bibliometric analysis on serendipity research using bibliometric tools in library and information science studies. The paper would definitely open new avenues for other serendipity researchers.

Recent studies have observed rise in consumer’s ethical concerns about the online retailers while making a purchase decision. The impetus for businesses to use corporate social responsibility (CSR) is evident, but the effects of CSR motives on corresponding processes underlying cause-related marketing (CRM) patronage intention have not been thoroughly examined. This study, anchored on attribution theory, established a research model that better explains the influence of CSR motives on patronage intentions toward CRM-oriented online retailers. Additionally, this study aims to examine the moderating role of spirituality (SPT) on CSR motives and CRM patronage intention (CPI).

Primary data has been collected from 722 respondents and analyzed by using deep neural-network architecture by using the innovative PLS-SEM-ANN method to predict/rank the factors impacting CPI.

The results revealed the normalized importance of the predictors of CPI and found that value-driven motive was the strongest predictor, followed by strategic motive, SPT, age and stakeholder-driven motive. In contrast, egoistic motive, education and income were found insignificant.

The pandemic has transformed the way consumers shop and fortified the online economy, thereby resulting in a paradigm shift toward usage of e-commerce platforms. The results offer valuable insights to online retailers and practitioners for predicting patronage intentions by CSR motives and, thus, effectively engage CRM consumers by designing promotions in a way that would deeply resonate with them. This study assessed and predicted the factors influencing the CPI s, thereby guiding the online retailers to design CSR strategies and manage crucial CRM decisions.

Drawing on new insights from the perspectives and experiences of board members, the purpose of this study is to determine the board attributes that influence board roles in improving the integration of corporate social responsibility (CSR) into corporate governance structures. In total, 10 in-depth semi-structured interviews were conducted with directors of listed Jordanian companies to explore their perceptions of the effect of board of directors' composition on CSR and CSR disclosure (CSRD). The key findings show that boards with a diverse range of directors is essential independent/nonexecutive members, directors with business and/or accounting backgrounds, and foreign members to determine if they aim to better manage their CSR. To take CSR to the next level in the Arab region, we need to strengthen corporate governance mechanisms, and put more pressures on companies to make changes in board composition. For example, we suggest that companies that appoint business-educated and foreign members to their boards tend to engage in more impactful social and environmental-related activities and reflect their sustainable development more effectively. The study responds to calls for further research adopting qualitative methods, such as case studies and interviews in order to obtain a complete and in-depth understanding of the influence of board composition on CSR/CSRD. The findings provide useful insights for practice, policymakers, and future research.

Recreational scuba diving is one of the fastest growing tourism industries around the world and has become a popular activity in Taiwan. Few studies focus on enduring involvement with a high risk or difficult activity specialization, so this study aims to explore the causal relationship between enduring involvement and specialization and seeks to explain sustained involvement in scuba diving activity as a recreation specialization.

This research selects four diving sites in Taiwan as survey locations, specifically Yeliou, Longdong, Kenting and Green Island. The questionnaire consists of three sections, including demographic information, enduring involvement and specialization. By analyzing the data collected from 810 scuba divers in Taiwan, structural equation modeling is used to examine the causal relationships among the variables.

The primary findings of this study are as follows: attraction positively affects divers’ commitment and lifestyle through joy, relaxation and sharing diving experiences; the results indicate that self-expression is associated with past experience of participating in scuba diving activity; and centrality indicates that participants’ daily life and recreation are related to each other and become central to their life. Results show that most theoretical hypotheses are supported, but there is no significant evidence of attraction impacting past experience or self-expression influencing commitment and lifestyle.

To the best of the authors’ knowledge, this study is the first to examine the causal influence of enduring involvement and specialization in the scuba diving context. The findings provide a solid theoretical basis for the study of sustained involvement motivation and behavior on specialization. Implications and recommendations for future research are discussed.

休闲水肺潜水是全球发展最快的旅游业之一, 已成为台湾的热门活动。很少有研究关注持续涉入高风险或困难活动的专门化, 因此本研究探讨持续涉入和专门化之间的因果关系, 并试图解释持续参与水肺潜水活动作为休闲专门化。

这项研究选择了台湾的四个潜水地点作为调查地点, 特别是野柳, 龙洞, 垦丁和绿岛。问卷分为三个部分, 包括人口统计信息, 持续参与和专门化。通过分析从台湾810名潜水员那里收集的数据, 使用结构方程模型检查变量之间的因果关系。

这项研究的主要发现是：（1）吸引力通过愉悦, 放松和分享潜水经历积极影响潜水员的承诺和生活方式; （2）结果表明自我表达与过去参加水肺潜水活动的经历有关（3）中心性表示参与者的日常生活和娱乐彼此相关, 并成为他们生活的中心。结果表明, 大多数理论假设均得到支持, 但没有显着证据表明吸引力会影响过去的经历或自我表达影响承诺和生活方式。

据我们所知, 本研究是第一个研究在潜水环境中持续涉入和专门化的因果关系影响的研究。研究结果为专门化持续参与动机和行为的研究提供了坚实的理论基础。 讨论了对未来研究的影响和建议。

El buceo recreativo es una de las industrias turísticas de más rápido crecimiento en todo el mundo y se ha convertido en una actividad popular en Taiwán. Pocos estudios se centran en la participación duradera con una especialización de actividad difícil o de alto riesgo, por lo que este estudio explora la relación causal entre la participación duradera y la especialización y busca explicar la participación sostenida en la actividad de buceo como una especialización recreativa.

Esta investigación selecciona cuatro sitios de buceo en Taiwán como lugares de estudio, específicamente Yeliou, Longdong, Kenting y Green Island. El cuestionario consta de tres secciones, que incluyen información demográfica, participación duradera y especialización. Al analizar los datos recopilados de 810 buzos en Taiwán, se utiliza un modelo de ecuaciones estructurales para examinar las relaciones causales entre las variables.

Los hallazgos principales de este estudio son: (1) la atracción afecta positivamente el compromiso y el estilo de vida de los buceadores a través de la alegría, la relajación y el intercambio de experiencias de buceo, (2) los resultados indican que la autoexpresión está asociada con la experiencia pasada de participar en actividades de buceo., y (3) la centralidad indica que la vida diaria y la recreación de los participantes están relacionadas entre sí y se vuelven centrales en su vida. Los resultados muestran que la mayoría de las hipótesis teóricas están respaldadas, pero no hay evidencia significativa de que la atracción afecte la experiencia pasada o la autoexpresión que influya en el compromiso y el estilo de vida.

Hasta donde sabemos, este estudio es el primero en examinar la influencia causal de la participación y la especialización duraderas en el contexto del buceo. Los hallazgos proporcionan una base teórica sólida para el estudio de la motivación y el comportamiento de participación sostenida en la especialización. Se discuten las implicaciones y recomendaciones para futuras investigaciones.

This study aims to investigate how employee perspectives on the role of business, specifically capitalist beliefs, affect the corporate social responsibility (CSR)–reputation–employee behavior relationship.

A conceptual model was developed, and to test the model empirically, survey data were collected over two phases from 192 working professionals. Data were analyzed in SAS using Hayes’s PROCESS approach.

Results of this study reveal that the positive employee outcomes (i.e. affective commitment and reduced turnover intentions), resulting from CSR, through perceived employer reputation (i.e. an employee’s perception of how others view their firm), are diminished when employees have strong capitalist beliefs.

Building on the signaling and person–organization fit literatures, this study highlights the theoretical and managerial importance of recognizing employees’ ideological differences as well as the value of considering employee perceptions of reputation. Although many stakeholders value social responsibility, not all do, and a firm’s intended outcomes will vary depending on employees’ beliefs.

This study demonstrates that CSR not only affects institutional-level corporate reputation, as previously studied, but also affects employees’ behaviors through “perceived employer reputation”, or employee beliefs about how other stakeholders perceive the firm. Moreover, this study highlights the importance of understanding employee differences, including ideological differences, prior to engaging in certain types of CSR.