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Background: The annual average daily traffic (AADT) data from road segments are critical for roadway projects, especially with the decision-making processes about operations, travel demand, safety-performance evaluation, and maintenance. Regular updates help to determine traffic patterns for decision-making. Unfortunately, the luxury of having permanent recorders on all road segments, especially low-volume roads, is virtually impossible. Consequently, insufficient AADT information is acquired for planning and new developments. A growing number of statistical, mathematical, and machine-learning algorithms have helped estimate AADT data values accurately, to some extent, at both sampled and unsampled locations on low-volume roadways. In some cases, roads with no representative AADT data are resolved with information from roadways with similar traffic patterns.

Methods: This study adopted an integrative approach with a combined systematic literature review (SLR) and meta-analysis (MA) to identify and to evaluate the performance, the sources of error, and possible advantages and disadvantages of the techniques utilized most for estimating AADT data. As a result, an SLR of various peer-reviewed articles and reports was completed to answer four research questions.

Results: The study showed that the most frequent techniques utilized to estimate AADT data on low-volume roadways were regression, artificial neural-network techniques, travel-demand models, the traditional factor approach, and spatial interpolation techniques. These AADT data-estimating methods' performance was subjected to meta-analysis. Three studies were completed: R squared, root means square error, and mean absolute percentage error. The meta-analysis results indicated a mixed summary effect: 1. all studies were equal; 2. all studies were not comparable. However, the integrated qualitative and quantitative approach indicated that spatial-interpolation (Kriging) methods outperformed the others.

Conclusions: Spatial-interpolation methods may be selected over others to generate accurate AADT data by practitioners at all levels for decision making. Besides, the resulting cross-validation statistics give statistics like the other methods' performance measures.

The proliferation of technological advancements has facilitated unrestricted access to and customizable consumption of content for viewers. Over-the-top (OTT) services are becoming more and more popular as the number of people using video streaming services grows around the world. In this context, this study aims to identify the antecedents and outcomes of Customer over-the-top Experience (COTTE) by synthesizing the existing research.

This research used the systematic literature review approach to identify the antecedents and outcomes of COTTE, along with the publication schedule, theories, analytical techniques, research methodology, and geographic scope of the 47 studies identified from the Scopus and Web of Science database.

The findings elucidate various antecedents of COTTE, including user-related, social, content-related, and website/platform-related factors. Additionally, diverse outcomes, encompassing behavioural/attitudinal and company-related factors have been discussed. Furthermore, an integrated framework is presented herein, synthesizing extant research and guiding future researchers in this domain.

The study’s findings offer a novel perspective for service providers aiming to enhance the OTT experience for their customers. This study stands out as one of the first to comprehensively present the antecedents and consequences of COTTE.

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.

This study aims to research the development trend, research status, research results and existing problems of the steel–concrete composite joint of railway long-span hybrid girder cable-stayed bridge.

Based on the investigation and analysis of the development history, structure form, structural parameters, stress characteristics, shear connector stress state, force transmission mechanism, and fatigue performance, aiming at the steel–concrete composite joint of railway long-span hybrid girder cable-stayed bridge, the development trend, research status, research results and existing problems are expounded.

The shear-compression composite joint has become the main form in practice, featuring shortened length and simplified structure. The length of composite joints between 1.5 and 3.0 m has no significant effect on the stress and force transmission laws of the main girder. The reasonable thickness of the bearing plate is 40–70 mm. The calculation theory and simplified calculation formula of the overall bearing capacity, the nonuniformity and distribution laws of the shear connector, the force transferring ratio of steel and concrete components, the fatigue failure mechanism and structural parameters effects are the focus of the research study.

This study puts forward some suggestions and prospects for the structural design and theoretical research of the steel–concrete composite joint of railway long-span hybrid girder cable-stayed bridge.

The physical internet (PI) is an emerging logistics and supply chain management (SCM) concept that draws on different technologies and areas of research, such as the Internet of Things (IoT) and key performance indicators, with the purpose of revolutionizing existing logistics and SCM practices. The growing literature on the PI and its noteworthy potential to be a disruptive innovation in the logistics industry call for a systematic literature review (SLR), which we conducted that defines the current state of the literature and outlines future research directions and approaches.

The SLR that was undertaken included journal publications, conference papers and proceedings, book excerpts, industry reports and white papers. We conducted descriptive, citation, thematic and methodological analyses to understand the evolution of PI literature.

Based on the literature review and analyses, we proposed a comprehensive framework that structures the PI domain and outlines future directions for logistics and SCM researchers.

Our research findings are limited by the relatively low number of journal publications, as the PI is a new field of inquiry that is composed primarily of conference papers and proceedings.

The proposed PI-based framework identifies seven PI themes, including the respective facilitators and barriers, which can inform researchers and practitioners on future potentially disruptive SC strategies.

The concept of hinterland is changing with a globalized economy, new needs between airports, stakeholders and the tourist destination challenge new dimensions of operation in the territory. Identifying new factors and actors in the influence zone of the hinterland will allow us to stage the importance of airports in the regional economy and the positive effects derived from these. The aim of this paper is to analyse the hinterland of Málaga Costa del Sol airport and its territorial and economic dimensions. Moreover, to provide an updated and clearer definition of hinterland, assuming future implications for airport operators, management of tourist destination by destination marketing organizations and scholars and practitioners interested in this topic. The results revealed that Málaga’s airport is modifying the hinterland of airport and its area of influence in economic and urban development terms.

Several freight operations rely on human cognition and behavior. Tackling these aspects, gamification transforms activities to resemble game-like experiences. Since the freight transportation sector is rapidly adopting gamification, the purpose of this study is to provide an overview that synthesizes the state-of-the-art and plot future directions for research and the practice of gamifying this area.

A systematic review of the gamification of freight transportation was conducted. After screening 691 studies, 40 relevant studies were analyzed.

Most studies found positive psychological and behavioral outcomes from gamification. Literature mainly focused on tackling the operational-level issues of road and maritime transportation modes by implementing simulation games.

Besides elaborating how gamification can improve freight transportation, the authors describe directions still uncovered by the current corpus, such as research design and temporality and the variety of modes and tasks.

Practical implications emerged from the studies, primarily focusing on understanding users, tasks and contexts, targeting different audiences and transportation modalities, and balancing motivational affordances, while considering the demands of the freight transportation domain, including dynamic, spatially dispersed environments and cooperation between multiple stakeholders.

The transportation of goods dominates much of the global economy and ecology. Therefore, gamifying this domain has a huge societal impact potential, especially related to issues of sharing economy, safety, environmental sustainability and social media.

Beyond providing an original overview of gamified freight transportation, this study maps current research gaps and describes practical recommendations.

Uncertainty management (UM) in projects has been a point of attention for researchers for many years. Research on UM has mainly been aimed at uncertainty analyses in the front-end and managing uncertainty in the construction phase. In contrast, UM components in the design phase have received less attention. This research aims to improve knowledge about the key components of UM in the design phase of large road projects.

This study adopted a literature review and case study. The literature review was used to identify relevant criteria for UM. These criteria helped to design the interview guide. Multiple case study research was conducted, and data were collected through document study and interviews with project stakeholders in two road projects. Each case's owners, contractors and consultants were interviewed individually.

The data analysis obtained helpful information on the involved parties, process and exploit tools and techniques during the design phase. Johansen's (2015) framework [(a) human and organisation, (b) process and (c) tools and techniques)] was completed and developed by identifying relevant criteria (such as risk averse or risk-taker, culture and documentation level) for each component. These criteria help to measure UM performance. The authors found that owners and contractors are major formal UM actors, not consultants. Empirical data showed the effectiveness of Web-based tools in UM.

The studied cases were Norwegian, and this study focussed on uncertainties in the project's design phase. Relevant criteria did not cover all the criteria for evaluating the performance of UM. Qualitative evaluation of criteria allows further quantitative analysis in the future.

This paper gave project owners and managers a better understanding of relevant criteria for measuring UM in the owners and managers' projects. The paper provides policy-makers with a deeper understanding of creating rigorous project criteria for UM during the design phase. This paper also provides a guideline for UM in road projects.

This research gives a holistic evaluation of UM by noticing relevant criteria and criteria's interconnection in the design phase.

This paper defines the emerging intermodal issues, identifies alternative solutions and develops strategies to achieve them. It reviews intermodal logistics policies in the EU, NAFTA and Asia, focusing on the United States and Japan in NAFTA and Asia respectively, because they have been the prominent motors of international trade in their regions. From an Asian standpoint, it is a pity that it is not yet possible to report on a common intermodal strategy.

The present study reviews the literature on the history and evolution of investment strategies in the stock market for the period from 1900 to 2022. Conflicts and relationships arising from such diverse seminal studies have been identified to address the research gaps.

The studies for this review were identified and screened from electronic databases to compile a comprehensive list of 200 relevant studies for inclusion in this review and summarized for the cognizance of researchers.

The study finds a coherence to complex theoretical documentation of more than a century of evolution on investment strategy in stock markets, capturing the characteristics of time with a chronological study of events.

There were complications in locating unpublished studies leading to biases like publication bias, the reluctance of editors to publish studies, which do not reveal statistically significant differences, and English language bias.

Practitioners can refine investment strategies by incorporating behavioral finance insights and recognizing the influence of psychological biases. Strategies span value, growth, contrarian, or momentum indicators. Mitigating overconfidence bias supports effective risk management. Social media sentiment analysis facilitates real-time decision-making. Adapting to evolving market liquidity curbs volatility risks. Identifying biases guides investor education initiatives.

This paper is an original attempt to pictorially depict the seminal works in stock market investment strategies of more than a hundred years.