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Common literature review methods such as systematic review and narrative review are poorly suited to the investigation of complex management phenomena. Systematic reviews are highly driven by protocol and procedure, and are oft-criticized as reductive and poorly equipped to examine the interaction between phenomena and context, nonlinear processes, and empirical outcomes that are less predictable. Narrative reviews, on the other hand, are pluralistic and iterative and thus better suited to descriptions of the complex and unpredictable; however, they tend to lack methodological transparency, trustworthiness, and pragmatism in application. The “realist synthesis” approach to literature review can be seen as the middle-ground between these two common methods, offering both methodological rigor alongside flexibility and nuance. Realist synthesis takes an explanatory frame, with a focus on unearthing the theorized causal mechanisms at play beneath a phenomenon of interest.

Challenges associated with ensuring the accuracy and reliability of cost estimation of highway construction bid items are of significant interest to state highway transportation agencies. Even with the existing research undertaken on the subject, the problem of inaccurate estimation of highway bid items still exists. This paper aims to assess the accuracy of the cost estimation methods employed in the selected studies to provide insights into how well they perform empirically. Additionally, this research seeks to identify, synthesize and assess the impact of the factors affecting highway unit prices because they affect the total cost of highway construction costs.

This paper systematically searched, selected and reviewed 105 papers from Scopus, Google Scholar, American Society of Civil Engineers (ASCE), Transportation Research Board (TRB) and Science Direct (SD) on conceptual cost estimation of highway bid items. This study used content and nonparametric statistical analyses to determine research trends, identify, categorize the factors influencing highway unit prices and assess the combined performance of conceptual cost prediction models.

Findings from the trend analysis showed that between 1983 and 2019 North America, Asia, Europe and the Middle East contributed the most to improving highway cost estimation research. Aggregating the quantitative results and weighting the findings using each study's sample size revealed that the average error between the actual and the estimated project costs of Monte-Carlo simulation models (5.49%) performed better compared to the Bayesian model (5.95%), support vector machines (6.03%), case-based reasoning (11.69%), artificial neural networks (12.62%) and regression models (13.96%). This paper identified 41 factors and was grouped into three categories, namely: (1) factors relating to project characteristics; (2) organizational factors and (3) estimate factors based on the common classification used in the selected papers. The mean ranking analysis showed that most of the selected papers used project-specific factors more when estimating highway construction bid items than the other factors.

This paper contributes to the body of knowledge by analyzing and comparing the performance of highway cost estimation models, identifying and categorizing a comprehensive list of cost drivers to stimulate future studies in improving highway construction cost estimates.

The purpose of this research is to undertake a bibliometric analysis of digital marketing research in small and medium enterprises (SMEs). The study examines papers over the last two decades and performed performance analysis, co-citation analysis, bibliographic coupling and scientific mapping.

The study examines 247 documents retrieved from the Scopus database using bibliometric analysis, performance analysis and thematic clustering. The study looked at the scientific productivity of papers, prolific authors, most influencing papers, institutions and nations, keyword co-occurrence, thematic mapping, co-citations and authorship and country collaborations. VOSviewer was employed as a tool in the research to conduct the performance analysis and thematic clustering.

The most productive year was 2021 with 56 publications and the most impactful institute and countries are the University of Birmingham, UK, and the country is United Kingdom, respectively. Similarly, the most influential journal is “Industrial Marketing Management”, and the most productive journal is “International Journal of Internet Marketing and Advertising”. Furthermore, the most cited article is “Usage, barriers and measurement of social media marketing: An exploratory investigation of small and medium B2B brands”. The authors also identified five thematic clusters of digital marketing research in SMEs.

It informs and directs researchers on the current state of study in the field of digital marketing literature in SMEs. It also outlines future research directions in this field.

This is the first study which provides the performance analysis and scientific mapping of the digital marketing literature in SMEs.