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Will COVID “encourage” B2B and data exchange engineering in logistic firms?

  • Libor Šimek EMAIL logo and Václav Cempírek
Published/Copyright: February 7, 2024
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Open Engineering
From the journal Open Engineering Volume 14 Issue 1

Abstract

The goal of this article is to develop recommendations to assist logistic companies in formulating their B2B deployment policies as part of their engineering infrastructure strategy. It is postulated that logistic firms are likely to integrate B2B into their organizational structure in order to obtain a competitive advantage. The research examines the situation not only in the period immediately prior (2006) and after (2010) the 2008–2009 economic crisis, but also over a longer period of the following years in order to discover an eventual impact of the crisis on B2B deployment (2014, 2018). The results obtained from the 2008–2009 economic crisis are then applied analogically to the current 2020 coronavirus economic recession, where they serve as a foundation for formulating B2B deployment policy recommendations. We ascertained that B2B deployment increases in time of intensified market competition due to an economic crisis or recession and this tendency persists even in a longer horizon after the macroeconomic instability culmination. B2B systems can thus act as a significant “tool” for enhancing business competitiveness, which may be crucial for their economic “survival.”

Keywords: engineering; data exchange; B2B; logistics; COVID

1 Introduction

If any logistic firm is to operate efficiently and profitably, all its internal procedures must be conceived up to date with the most advance engineering standards [1]. These may apply to all the latest engineering trends, such as those in robotization, automation, and optimation of logistic processes, organizing intermodal transport into chains, advanced transport systems, systems of autonomous mobility, innovations in the field of transport and storage systems, logistic process simulation in practice, development of logistic processes as a source of competitive advantage, promotion of environmental aspect in technology [2], and – last but not least – deployment and maintaining of the systems for inter-business integration B2B, which provide a technical “background” and infrastructure for efficient data exchange between individual logistic business entities [3].

The most important advantage of B2B is consistent improvement of internal business processes, decrease of the risk of mistakes, formation and integration of strategic relationships, and reduction of the firm’s operational expenses [4]. Numerous firms associate in interconnected and integrated chains, where a procurement supply chain management system is used, in consequence of the pressure to reduce operational costs.

The firm’s decision on whether or not to implement B2B makes it necessary to “switch” to a new platform of communication with its business associates, as well as to carry out a change of work practices and make a new definition of employee responsibilities. This decision may provide an opportunity to acquire a good reputation with business partners. For this reason, it is a tactical decision that can only be made by the firm’s top management, and it necessitates a strategic study to be carried out [5].

The aforementioned system especially applies to the firms engaged in logistic activities. That is due to worldwide anti-epidemic actions fighting coronavirus disease (COVID), which are targeted to stop propagation of the disease. COVID’s worldwide character necessitated a variety of actions to mitigate the disease’s harmful effects, obstructing otherwise trouble-free movements of goods and people and erecting “new” obstacles to free trade and transport of goods. As a result, it is apparent that these policies had extremely negative worldwide economic consequences, particularly in the sector of logistic entrepreneurial activities [6]. As a consequence, the coronavirus disease forced a large number of logistic firms to fight with their market competitors, which made it necessary to (fully) deploy all available technical and engineering means available up to now, including sophisticated supply chain coordination systems, one of which is B2B. As a result, it is evident that determining the most appropriate B2B policy may be a significant weapon for economic growth in COVID period, to which this article aspires to contribute.

2 Problem solved

The goal of this study is to provide B2B policy recommendations with the intent of enhancing competitiveness of logistic firms during the economic downturn. This focus is justified by the fact that logistics is unquestionably one of the entrepreneurial industries most adversely affected by current anti-COVID policies.

The first stage of the research consists in determining the level of B2B deployment (hereafter “deployment”) with logistic enterprises during the crisis of 2008–2009. The second stage aims to ascertain whether there is any data making us believe that the 2008–2009 crisis had an impact on how often the logistic firms in the Czech Republic deploy B2B in their business operations. In the last stage, the findings drawn from the 2008–2009 crisis will analogously be applied to the current 2020 COVID economic recession, and realistic B2B deployment instructions will be formulated.

3 Research hypotheses

We developed a general hypothesis, which postulates that B2B deployment increases in time of intensified market competition, i.e., economic crisis or recession, and this tendency continues even in a longer time horizon after the macroeconomic instability culmination. In order to verify the aforementioned general hypothesis, this was decomposed into two partial hypotheses as given below, whose aim was to detect a year-on-year change in B2B deployment across the period of the 2008–2009 economic crisis. According to the analytic approach outlined as follows, these two hypotheses are mutually interrelated and constitute a hierarchically organized system. As a result, Hypothesis 2 is a modification of Hypothesis 1.

Hypothesis 1: The degree to which firms deployed B2B in 2006 differed from that in 2010, which may be ascribed to the fact that some of them – in reality – modified their B2B deployment approach.

Hypothesis 2: Hypothesis 1’s difference may be observed not only between the years 2006 and 2010, but also over a longer period of time, i.e., between the years 2014 and 2018.

4 Methods

4.1 Data collection

About 216 firms (corporate entities headquartered in the Czech Republic; source: Albertina Database of Firms – Company Monitor) were asked four questions during a telephone inquiry (this form was chosen because of an expected higher information return). “What B2B deployment did your firm apply within its organization structure in 2006/2010/2014/2018?” The respondents had the possibility to choose from two alternative responses for each of the questions above: “none” or “full.”

4.2 Data analysis

The input data entered into analysis is specified in Annex. For verification of Hypothesis 1, we used the full deployment percentages ascertained for the year 2006 (26.92%) versus 2010 (58.97%). For verification of Hypothesis 2, we entered the full deployment percentages ascertained for years 2006 (37.04%), 2010 (44.44%), 2014 (32.65%), and 2018 (34.69).

The mathematical apparatus, i.e., statistical tests, applied for analysis is specified in the contingency table (Annex) depending on the given relationships between the samples compared. The analysis design is based on three analytical dimensions and the three categorical variables that correspond to them (inter-sample correlation, number of years compared, and number of response alternatives), each of which can acquire just two values (binomial categorical variable). By combining these three variables, we come to eight mutually different inter-relations between the compared samples as visually displayed in the three-way contingency table (Annex). For the verification of Hypothesis 1, where two dependent (identical) samples of firms were compared, we used McNemar test, Wald Z test, and Nam score test. For verifying Hypothesis 2, where four dependent samples of firms were compared, we applied Cochran Q test, minimum required absolute difference test, and McNemar test asymptotic/binomial.

5 Results

Annex presents the data obtained from the respondents (logistic firms). Sectioning is used to render the data structure, which conforms to the overall analysis design. Annex also shows a comprehensive list of the tests performed and the corresponding resulting test data (p-values).

5.1 Hypothesis 1 (Annex C)

In this scenario, two B2B deployment percentages (i.e., across two years: 2006 vs 2010) are compared, there are two deployment alternatives (none vs full), and the compared samples are identical (i.e., the samples contain the same firms).

In order to detect a hypothesized difference in B2B deployment percentages (hereinafter also “percentage”) across the examined years (2006 vs 2010) in a statistically reliable manner, two auxiliary hypotheses were formulated, each of which represents the difference in the percentages in a different manner, which may lead to conflicting test results:

  1. Difference in percentages (obtained by subtracting): H01: “P 2006 – P 2010 = 0” (where P represents the B2B deployment percentage)

  2. Ratio of the percentages: H02: “P 2006/P 2010 = 1”

The aforementioned two auxiliary hypotheses were rejected, which means that Hypothesis 1 was verified in a statistically reliable manner. Because the samples analyzed within the verification of this hypothesis are identical (they comprise the same firms), we can conclude that the change in B2B deployment detected factually consists in a change in the corporate practices of the firms.

5.2 Hypothesis 2 (Annex G)

Like in the scenario of Hypothesis 1 in the previous section, there are two deployment alternatives (none vs full) and the compared samples are identical (i.e., the samples contain the same firms). However, in the actual scenario of Hypothesis 2, four) B2B deployment percentages (i.e., across 4 years: 2006 vs 2010 vs 2014 vs 2018) are compared (unlike Hypothesis 1, where only 2 years, i.e., two samples, was compared).

5.2.1 Basic test

The auxiliary hypothesis H0: “P 2006 = P 2010 = P 2014 = P 2018” was rejected, which means that Hypothesis 2 was verified. Because the samples compared within verification of this hypothesis are identical (they contain the same firms), we can conclude that the difference in B2B deployment detected factually consists in a change of corporate practices, as mentioned in section testing Hypothesis 1. The most important ascertainment is that because we compared four company samples in Hypothesis 2 (2006 vs 2010 vs 2014 vs 2018), the difference detected in B2B deployment within the verification of Hypothesis 1 persisted even over a longer span of time, i.e., until 2018.

5.2.2 Post hoc test (multiple comparison)

The auxiliary hypothesis H0: “The B2B deployment percentages are equal in the given pair of compared years (P YR ᵢ = P YR j)” was rejected only in case of two pairs of years: 2006 vs 2018 and 2014 vs 2018. This means that the difference in B2B deployment percentages detected in the aforementioned basic test exclusively consists in the difference within these two pairs of the compared years. Note: the verification test was performed on an individual level of statistical significance of α IND = 0.05/6 = 0.0083 (Bonferroni correction was applied: α OVERALL/number of combinations of all the pairs compared).

The results obtained can be summarized as follows: we detected a statistically significant difference in B2B deployment between the years 2006 versus 2010, which means that there was a considerable increase of B2B deployment across the period of the 2008 economic crisis. A statistically significant difference in B2B deployment was detected not only in the short-term period as stated earlier, but even in a long-term prospect, i.e., in the years following the crisis up to the year 2018.

6 Conclusion

The ascertainments related to the 2008–2009 economic crisis will analogically be translated to the period of the 2020 coronavirus economic recession, and recommendations for B2B deployment strategy will be formulated accordingly.

Recommendation 1: The data obtained (Annex C) demonstrate that in 2010, B2B was deployed by 58.97% of logistic firms, implying that B2B deployment was widespread. As a result, we may advise logistic firms to aggressively implement and use B2B, since the aforementioned high rates demonstrate the importance of B2B in business operations [7]. This means that ignoring B2B deployment might result in a logistic firm missing out on a great chance to catch up with the newest management practices and enhance its (international) competitiveness [8].

Recommendation 2: If comparing the years 2006 vs 2010, and only considering two deployment alternatives (“none” vs “full”), the data obtained show (Figure 1) that the change in B2B deployment occurred in 57.69% (i.e., more than half of) the logistic firms, with 44.87% starting to deploy B2B and – on the contrary – 12.82% discontinuing B2B. The resulting balance of these two opposing shifts is 32.05% in favor of B2B deployment.

Figure 1 B2B deployment [2006 vs 2010] Source: own. Firm count: percentage of the respondents in year (absolute count is given in parentheses).
Figure 1

B2B deployment [2006 vs 2010] Source: own. Firm count: percentage of the respondents in year (absolute count is given in parentheses).

Based on the successful verification of Hypothesis 1, we conclude that there must be a change in B2B deployment between the year preceding (2006) and the year following (2010) the 2008–2009 economic crisis. The identified year-on-year change in the degree of B2B deployment (2006 vs 2010) is due to a “modification” of corporate practices, not to a year-on-year change in the structure of these two mutually compared samples of firms, because these two samples contain the same firms. This suggests that the difference in B2B deployment was not attributable to the false assumption that, following the 2008–2009 economic crisis, more firms favoring B2B deployment should be established as confirmed by other studies [9]. On the contrary, we may infer that the change in B2B deployment was proved to be due to a real change of the B2B attitude “inside” the logistic firms themselves.

Based on the foregoing findings, we recommend that, in time of macroeconomic instability, the stress on B2B deployment in operations of logistic firms should be accentuated even more than stated in Recommendation 1. It is because the higher level of B2B deployment ascertained during the 2008–2009 economic crisis revealed that the logistic firms – most probably as a result of intensified market competition – recognized the importance of B2B and were forced to deploy it in order to increase the probability of their “surviving” under global economy pressure. Another indication of B2B importance for corporate operations, as indicated in Recommendation 1, is the dynamic character of B2B deployment (differences in B2B implementation over the time of economic instability).

Recommendation 3: The data obtained (Annex G) show that in 2006, B2B was deployed by 37.04% of the logistics firms (which provided the data for all the four years examined) and in 2010, this number even increased to 44.44%; however, it dropped to 32.65% in 2014 and rose moderately to 34.69% in 2018. This means that B2B deployment considerably increased shortly after culmination of the 2008–2009 economic crisis, however moderately decreased in the following years.

Following the successful verification of Hypothesis 2, we conclude that the difference in B2B deployment was ascertained not only over a short period of the two compared years (i.e., 2006 vs 2010, which are the years immediately preceding and following the 2008–2009 economic downturn), as postulated in Hypothesis 1. On the contrary, the difference was contrarily proved even in an extended time period following the crisis culmination, spanning over 4 years in total (2006 vs 2010 vs 2014 vs 2018). However, the post hoc test revealed that the difference detected in the basic test exclusively consists in the difference within two pairs of the mutually compared years (2006 vs 2018; 2014 vs 2018).

In case of testing both Hypothesis 1 and Hypothesis 2, we always compared identical samples of logistic firms. This means that the differences detected in B2B deployment, in reality, consist in a “change” in the operational practices of the logistic firms. However, in case of Hypothesis 2, this change was proved not only across a short period of time (2006 vs 2010), but even across a longer period following the crisis culmination, covering the years 2006 vs 2010 vs 2014 vs 2018. Thus, we can conclude that the difference in B2B deployment was ascertained even in a longer time horizon, persisting even in the years following the economic crisis.

Based on these findings, we recommend that the possibility of B2B deployment should be considered by the logistic firms not only in terms of a short time horizon (related to the actual economic instability), but also in terms of a longer time horizon (in the years after the instability). This is because, as previously stated, logistic firms (as any other organizations) have a propensity to modify their B2B deployment attitude also after elapsing a longer time, i.e., not just under the actual economic pressure during a crisis, but also in the years following the crisis [10]. This is true regardless of the fact that no trend in B2B implementation was observed across the 4 years compared, which means that the number of logistic firms with B2B deployed cannot be expected to increase in an uninterrupted line. However, the importance of B2B and the competitive advantage gained by its deployment may grow even long after the crisis has passed [11].

We can summarize the results obtained in this study within an extended scope of broader discussion to the sense that these are in a basic correspondence with ascertainments achieved by other authors in the respective field. The importance of B2B implementation is emphasized by a great number of studies [12,13,14]. They base their conclusions on the fact that B2B systems, in fact, serve as a fundament for all business functions, integrating all of its vital processes, be that procurement, storage, production, logistics, sales etc. [15]. Leek and Christodoulides [13] pointed out the fact that B2B creates a technical infrastructure, which is necessary for proper business operations. This is indirectly supported by Wiersema [16], who underlines the relationships between B2B and other business systems. In this respect, Wang and Cavusoglu [17] stated that B2B is fundamental for efficient maintenance of environmental management systems because systems of inter-business integration provide the necessary communication network. Lilien [18] pointed out the role of B2B systems for efficient and economical functioning of quality management systems, which has its source in the fact that B2B systems permeate the complete organizational structure of the business with a direct or indirect impact on quality. In the light of these facts, we can regard B2B systems as a crucial business component integrating the basis and vital organization functions [19]. This is supported by Swani et al. [20], who pointed out the strategic importance of B2B in a long-term business prospect, especially – as pointed out by Järvinen and Taiminen [14], and supported by results attained in our study – in time of intensified market competition, be that due to economic crisis or recession only.

Limitation of the research: In case of all of the inter-year comparisons, the tests were carried out with the only goal of detecting a hypothesized difference in B2B deployment. It is, however, important to remember that the differences detected in this manner, although statistically exactly and significantly, may not be due to the macroeconomic instability, i.e., the 2008–2009 economic crisis as the study assumes. On the contrary, man must consider also the possibility that the difference in B2B deployment could be caused by other factors [14], which are beyond the scope of this research and which are not identified and explained in this study.

Nonetheless, given the high reliability of the statistic tests performed (which included both exact and asymptotic variants in accordance with the principle of statistical multi-instrumentality), researchers can conclude that – at the very least – a portion of the differences ascertained can be attributed to the impact of the unstable macroeconomic environment, i.e., economic crisis. In light of the foregoing, the authors believe that the aforementioned recommendations, which were formulated by means of translating the conclusions drawn from an analysis of the situation during the 2008–2009 economic crisis to the current period of the 2020 COVID economic recession, have the capability to provide logistic firms – as market players and competitors – with useful advice on their policy of B2B deployment.

  1. Conflict of interest: Authors state no conflict of interest.

  2. Data availability statement: The data that support the findings of this study are available on request from the corresponding author.

Annex: Analysis design (tests) – B2B deployment (data obtained from respondents)

Count: % of the respondents in year (absolute count is given in parentheses). *1 – number of deployment alternatives; *2 – [p-value]; *3 – {detected difference}; α = 0.05; two-sided tests. Source: own.

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Received: 2022-02-14
Revised: 2023-10-17
Accepted: 2023-11-06
Published Online: 2024-02-07

© 2024 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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  100. Special Issue: AESMT-6
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  102. Forecasting empirical formula for suspended sediment load prediction at upstream of Al-Kufa barrage, Kufa City, Iraq
  103. Optimization and characterization of sustainable geopolymer mortars based on palygorskite clay, water glass, and sodium hydroxide
  104. Sediment transport modelling upstream of Al Kufa Barrage
  105. Study of energy loss, range, and stopping time for proton in germanium and copper materials
  106. Effect of internal and external recycle ratios on the nutrient removal efficiency of anaerobic/anoxic/oxic (VIP) wastewater treatment plant
  107. Enhancing structural behaviour of polypropylene fibre concrete columns longitudinally reinforced with fibreglass bars
  108. Sustainable road paving: Enhancing concrete paver blocks with zeolite-enhanced cement
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  113. An image encryption method based on modified elliptic curve Diffie-Hellman key exchange protocol and Hill Cipher
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  115. Effect of surface roughness on the interface behavior of clayey soils
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  117. Measurements of induced vibrations due to steel pipe pile driving in Al-Fao soil: Effect of partial end closure
  118. Experimental and numerical studies of ballistic resistance of hybrid sandwich composite body armor
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  120. Optimal design of mechanical performances of asphalt mixtures comprising nano-clay additives
  121. Advancing seismic performance: Isolators, TMDs, and multi-level strategies in reinforced concrete buildings
  122. Predicted evaporation in Basrah using artificial neural networks
  123. Energy management system for a small town to enhance quality of life
  124. Numerical study on entropy minimization in pipes with helical airfoil and CuO nanoparticle integration
  125. Equations and methodologies of inlet drainage system discharge coefficients: A review
  126. Thermal buckling analysis for hybrid and composite laminated plate by using new displacement function
  127. Investigation into the mechanical and thermal properties of lightweight mortar using commercial beads or recycled expanded polystyrene
  128. Experimental and theoretical analysis of single-jet column and concrete column using double-jet grouting technique applied at Al-Rashdia site
  129. The impact of incorporating waste materials on the mechanical and physical characteristics of tile adhesive materials
  130. Seismic resilience: Innovations in structural engineering for earthquake-prone areas
  131. Automatic human identification using fingerprint images based on Gabor filter and SIFT features fusion
  132. Performance of GRKM-method for solving classes of ordinary and partial differential equations of sixth-orders
  133. Visible light-boosted photodegradation activity of Ag–AgVO3/Zn0.5Mn0.5Fe2O4 supported heterojunctions for effective degradation of organic contaminates
  134. Production of sustainable concrete with treated cement kiln dust and iron slag waste aggregate
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  136. A comparative analysis of the energy dissipation efficiency of various piano key weir types
  137. Special Issue: Transport 2022 - Part II
  138. Variability in road surface temperature in urban road network – A case study making use of mobile measurements
  139. Special Issue: BCEE5-2023
  140. Evaluation of reclaimed asphalt mixtures rejuvenated with waste engine oil to resist rutting deformation
  141. Assessment of potential resistance to moisture damage and fatigue cracks of asphalt mixture modified with ground granulated blast furnace slag
  142. Investigating seismic response in adjacent structures: A study on the impact of buildings’ orientation and distance considering soil–structure interaction
  143. Improvement of porosity of mortar using polyethylene glycol pre-polymer-impregnated mortar
  144. Three-dimensional analysis of steel beam-column bolted connections
  145. Assessment of agricultural drought in Iraq employing Landsat and MODIS imagery
  146. Performance evaluation of grouted porous asphalt concrete
  147. Optimization of local modified metakaolin-based geopolymer concrete by Taguchi method
  148. Effect of waste tire products on some characteristics of roller-compacted concrete
  149. Studying the lateral displacement of retaining wall supporting sandy soil under dynamic loads
  150. Seismic performance evaluation of concrete buttress dram (Dynamic linear analysis)
  151. Behavior of soil reinforced with micropiles
  152. Possibility of production high strength lightweight concrete containing organic waste aggregate and recycled steel fibers
  153. An investigation of self-sensing and mechanical properties of smart engineered cementitious composites reinforced with functional materials
  154. Forecasting changes in precipitation and temperatures of a regional watershed in Northern Iraq using LARS-WG model
  155. Experimental investigation of dynamic soil properties for modeling energy-absorbing layers
  156. Numerical investigation of the effect of longitudinal steel reinforcement ratio on the ductility of concrete beams
  157. An experimental study on the tensile properties of reinforced asphalt pavement
  158. Self-sensing behavior of hot asphalt mixture with steel fiber-based additive
  159. Behavior of ultra-high-performance concrete deep beams reinforced by basalt fibers
  160. Optimizing asphalt binder performance with various PET types
  161. Investigation of the hydraulic characteristics and homogeneity of the microstructure of the air voids in the sustainable rigid pavement
  162. Enhanced biogas production from municipal solid waste via digestion with cow manure: A case study
  163. Special Issue: AESMT-7 - Part I
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  166. The effect of urban environment on large-scale path loss model’s main parameters for mmWave 5G mobile network in Iraq
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  170. In-depth analysis of critical factors affecting Iraqi construction projects performance
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  176. Estimation of the settlement of pile head using ANN and multivariate linear regression based on the results of load transfer method
  177. Enhancing communication: Deep learning for Arabic sign language translation
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  184. Evaluation of microstructure and mechanical properties of Al1050/Al2O3/Gr composite processed by forming operation ECAP
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  186. Investigation of in vitro behavior of composite coating hydroxyapatite-nano silver on 316L stainless steel substrate by electrophoretic technic for biomedical tools
  187. A review: Enhancing tribological properties of journal bearings composite materials
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  189. Design a new scheme for image security using a deep learning technique of hierarchical parameters
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  191. Comparative geotechnical analysis for ultimate bearing capacity of precast concrete piles using cone resistance measurements
  192. Visualizing sustainable rainwater harvesting: A case study of Karbala Province
  193. Geogrid reinforcement for improving bearing capacity and stability of square foundations
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  198. Special Issue: IETAS 2024 - Part I
  199. Analyzing the impact of transfer learning on explanation accuracy in deep learning-based ECG recognition systems
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  201. Improving multi-object detection and tracking with deep learning, DeepSORT, and frame cancellation techniques
  202. The impact of using prestressed CFRP bars on the development of flexural strength
  203. Assessment of surface hardness and impact strength of denture base resins reinforced with silver–titanium dioxide and silver–zirconium dioxide nanoparticles: In vitro study
  204. A data augmentation approach to enhance breast cancer detection using generative adversarial and artificial neural networks
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  206. Special Issue: 51st KKBN - Part I
  207. Evaluation of static bending caused damage of glass-fiber composite structure using terahertz inspection
https://doi.org/10.1515/eng-2022-0373
Keywords for this article
engineering; data exchange; B2B; logistics; COVID
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BY 4.0

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  126. Thermal buckling analysis for hybrid and composite laminated plate by using new displacement function
  127. Investigation into the mechanical and thermal properties of lightweight mortar using commercial beads or recycled expanded polystyrene
  128. Experimental and theoretical analysis of single-jet column and concrete column using double-jet grouting technique applied at Al-Rashdia site
  129. The impact of incorporating waste materials on the mechanical and physical characteristics of tile adhesive materials
  130. Seismic resilience: Innovations in structural engineering for earthquake-prone areas
  131. Automatic human identification using fingerprint images based on Gabor filter and SIFT features fusion
  132. Performance of GRKM-method for solving classes of ordinary and partial differential equations of sixth-orders
  133. Visible light-boosted photodegradation activity of Ag–AgVO3/Zn0.5Mn0.5Fe2O4 supported heterojunctions for effective degradation of organic contaminates
  134. Production of sustainable concrete with treated cement kiln dust and iron slag waste aggregate
  135. Key effects on the structural behavior of fiber-reinforced lightweight concrete-ribbed slabs: A review
  136. A comparative analysis of the energy dissipation efficiency of various piano key weir types
  137. Special Issue: Transport 2022 - Part II
  138. Variability in road surface temperature in urban road network – A case study making use of mobile measurements
  139. Special Issue: BCEE5-2023
  140. Evaluation of reclaimed asphalt mixtures rejuvenated with waste engine oil to resist rutting deformation
  141. Assessment of potential resistance to moisture damage and fatigue cracks of asphalt mixture modified with ground granulated blast furnace slag
  142. Investigating seismic response in adjacent structures: A study on the impact of buildings’ orientation and distance considering soil–structure interaction
  143. Improvement of porosity of mortar using polyethylene glycol pre-polymer-impregnated mortar
  144. Three-dimensional analysis of steel beam-column bolted connections
  145. Assessment of agricultural drought in Iraq employing Landsat and MODIS imagery
  146. Performance evaluation of grouted porous asphalt concrete
  147. Optimization of local modified metakaolin-based geopolymer concrete by Taguchi method
  148. Effect of waste tire products on some characteristics of roller-compacted concrete
  149. Studying the lateral displacement of retaining wall supporting sandy soil under dynamic loads
  150. Seismic performance evaluation of concrete buttress dram (Dynamic linear analysis)
  151. Behavior of soil reinforced with micropiles
  152. Possibility of production high strength lightweight concrete containing organic waste aggregate and recycled steel fibers
  153. An investigation of self-sensing and mechanical properties of smart engineered cementitious composites reinforced with functional materials
  154. Forecasting changes in precipitation and temperatures of a regional watershed in Northern Iraq using LARS-WG model
  155. Experimental investigation of dynamic soil properties for modeling energy-absorbing layers
  156. Numerical investigation of the effect of longitudinal steel reinforcement ratio on the ductility of concrete beams
  157. An experimental study on the tensile properties of reinforced asphalt pavement
  158. Self-sensing behavior of hot asphalt mixture with steel fiber-based additive
  159. Behavior of ultra-high-performance concrete deep beams reinforced by basalt fibers
  160. Optimizing asphalt binder performance with various PET types
  161. Investigation of the hydraulic characteristics and homogeneity of the microstructure of the air voids in the sustainable rigid pavement
  162. Enhanced biogas production from municipal solid waste via digestion with cow manure: A case study
  163. Special Issue: AESMT-7 - Part I
  164. Preparation and investigation of cobalt nanoparticles by laser ablation: Structure, linear, and nonlinear optical properties
  165. Seismic analysis of RC building with plan irregularity in Baghdad/Iraq to obtain the optimal behavior
  166. The effect of urban environment on large-scale path loss model’s main parameters for mmWave 5G mobile network in Iraq
  167. Formatting a questionnaire for the quality control of river bank roads
  168. Vibration suppression of smart composite beam using model predictive controller
  169. Machine learning-based compressive strength estimation in nanomaterial-modified lightweight concrete
  170. In-depth analysis of critical factors affecting Iraqi construction projects performance
  171. Behavior of container berth structure under the influence of environmental and operational loads
  172. Energy absorption and impact response of ballistic resistance laminate
  173. Effect of water-absorbent polymer balls in internal curing on punching shear behavior of bubble slabs
  174. Effect of surface roughness on interface shear strength parameters of sandy soils
  175. Evaluating the interaction for embedded H-steel section in normal concrete under monotonic and repeated loads
  176. Estimation of the settlement of pile head using ANN and multivariate linear regression based on the results of load transfer method
  177. Enhancing communication: Deep learning for Arabic sign language translation
  178. A review of recent studies of both heat pipe and evaporative cooling in passive heat recovery
  179. Effect of nano-silica on the mechanical properties of LWC
  180. An experimental study of some mechanical properties and absorption for polymer-modified cement mortar modified with superplasticizer
  181. Digital beamforming enhancement with LSTM-based deep learning for millimeter wave transmission
  182. Developing an efficient planning process for heritage buildings maintenance in Iraq
  183. Design and optimization of two-stage controller for three-phase multi-converter/multi-machine electric vehicle
  184. Evaluation of microstructure and mechanical properties of Al1050/Al2O3/Gr composite processed by forming operation ECAP
  185. Calculations of mass stopping power and range of protons in organic compounds (CH3OH, CH2O, and CO2) at energy range of 0.01–1,000 MeV
  186. Investigation of in vitro behavior of composite coating hydroxyapatite-nano silver on 316L stainless steel substrate by electrophoretic technic for biomedical tools
  187. A review: Enhancing tribological properties of journal bearings composite materials
  188. Improvements in the randomness and security of digital currency using the photon sponge hash function through Maiorana–McFarland S-box replacement
  189. Design a new scheme for image security using a deep learning technique of hierarchical parameters
  190. Special Issue: ICES 2023
  191. Comparative geotechnical analysis for ultimate bearing capacity of precast concrete piles using cone resistance measurements
  192. Visualizing sustainable rainwater harvesting: A case study of Karbala Province
  193. Geogrid reinforcement for improving bearing capacity and stability of square foundations
  194. Evaluation of the effluent concentrations of Karbala wastewater treatment plant using reliability analysis
  195. Adsorbent made with inexpensive, local resources
  196. Effect of drain pipes on seepage and slope stability through a zoned earth dam
  197. Sediment accumulation in an 8 inch sewer pipe for a sample of various particles obtained from the streets of Karbala city, Iraq
  198. Special Issue: IETAS 2024 - Part I
  199. Analyzing the impact of transfer learning on explanation accuracy in deep learning-based ECG recognition systems
  200. Effect of scale factor on the dynamic response of frame foundations
  201. Improving multi-object detection and tracking with deep learning, DeepSORT, and frame cancellation techniques
  202. The impact of using prestressed CFRP bars on the development of flexural strength
  203. Assessment of surface hardness and impact strength of denture base resins reinforced with silver–titanium dioxide and silver–zirconium dioxide nanoparticles: In vitro study
  204. A data augmentation approach to enhance breast cancer detection using generative adversarial and artificial neural networks
  205. Modification of the 5D Lorenz chaotic map with fuzzy numbers for video encryption in cloud computing
  206. Special Issue: 51st KKBN - Part I
  207. Evaluation of static bending caused damage of glass-fiber composite structure using terahertz inspection
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