Investigating the effects of barriers and challenges on Logistics 4.0 in the era of evolving digital technology

PurposeThis study aims to reveal and prioritize the main barriers and challenges in front of the Logistics 4.0 transformation, which is the extension of Industry 4.0. Also, this study presents a roadmap for a company operating in developing countries to reduce and eliminate challenges and hurdles for each link in their supply chain.Design/methodology/approachA two-stage methodology was used in this study. First, a detailed literature review was conducted to identify the barriers to innovations compatible with Industry 4.0. Hence, barriers have been identified, including nine from the literature review. The best-worst method (BWM) is then used to determine these barriers' weights and order of importance. To implement BWM, two-stage e-surveys are applied to experts.FindingsThe Managerial and Economic Challenges dimension is the most important, and Regulatory and social challenges is the least essential dimension among the main dimension. Moreover, financial constraints or capitals are the most critical barriers among the sub-barriers. This study gives the reader a comprehensive insight into how detected barriers affect digitalization performance. Therefore, this framework is a roadmap designed with a holistic view to guide manufacturers, logistics parties and even policy and decision-makers.Originality/valueTheoretically and empirically identifies the potential barriers and challenges in the digital transformation of logistics is already missing at the desired level. From this point of view, to the best of the authors' knowledge, this study is the first research that determines barriers based on the Logistics 4.0 model with an industrial perspective. One of the most important limitations of this study is that a total of nine dimensions were examined under only three basic barriers. Different alternatives can be identified for future studies.Managemen

Different types of approximation operators on Gn-CAS via ideals

A mathematical approach to dealing with the problems of ambiguity and indeterminacy in knowledge is called a rough set theory. It begins by using an equivalence relation to divide the universe into parts. Numerous generalized rough set models have been developed and investigated to increase their adaptability and extend their range of applications. In this context, we introduce new generalized rough set models that are inspired by covering-based rough sets and ideals. In this paper, lower and upper approximations of new types of covering rough sets based on j-neighborhoods, complementary j-neighborhoods, and j-adhesions are defined via ideals. The main features of these approximations are examined. The relationships among them are given by various examples and propositions. Some comparisons between our methods and others' methods such as Abd El-Monsef et al.'s method [2] and Nawar et al.'s method [22] are given. A practical example is given to illustrate one of our methods is more precise.Mathematics, Applied || Mathematic

Shock resistors or transmitters? Contagion across industries and countries during the COVID-19 pandemic and the global financial crisis

We examine how global shocks from various sources propagate across industries and countries. Financial contagion is measured using residual-based and volatility-adjusted correlation. Specific industries and countries were resilient during both global crises, while others played a significant role in transmitting shocks.Economic

Supply chain socially sustainability practices and their impact on supply chain performance: a study from the Indian automobile industry

While sustainability has been a well-researched area in academic literature, the performance impact of its social dimensions remains largely unexplored, especially in the context of emerging economies. The aim of this research paper is to test and validate the dimensions of supply chain social sustainability (SCSS) that firms should focus on and to examine the relationships between these practices and supply chain performance, both short term and long term. This paper adopts a questionnaire-based survey research approach in the context of Indian automobile industry. Empirical validation of the conceptual model developed was carried out using Confirmatory Factor Analysis. Multiple regression was used to test the relationships between SCSS practices and supply chain performance. This study finds empirical support to the proposition that a firm's initiatives on SCSS dimensions of safety, labour rights, ethical practices and welfare initiatives for people and their communities provide performance benefits to them and to their partners in the supply chains. Regression analysis revealed that safety (0.339) and labour rights (0.601) contribute to both short term and long term performance for the supply chain. While ethical practices have a positive impact on short term performance, welfare initiatives only provide long term qualitative benefits. SCSS is in evolving concept and adopting the right mix of factors can help firms to achieve sustainability in all three dimensions of the triple-bottom-line framework (People, Planet and Profit).Operations Research & Management Scienc

Erdogan's War: A Strongman's Struggle at Home and in Syria

Area Studie

Data fusion integrated network forecasting scheme classifier (DFI-NFSC) via multi-layer perceptron decomposition architecture

The Massive Access Problem of the Internet of Things stands for the access problem of the wireless devices to the Gateway when the device population in the coverage area is excessive. We develop a hybrid model called Data Fusion Integrated Network Forecasting Scheme Classifier (DFI-NFSC) using a Multi-Layer Perceptron (MLP) Decomposition architecture specifically designed to address the Massive Access Problem. We utilize our custom error metric to display throughput and energy consumption results. These results are obtained by emulating the Joint Forecasting-Scheduling (JFS) system on a single IoT Gateway and distinguishing between ARIMA, LSTM, and MLP forecasters of the JFS system. The outcomes indicate that the DFI-NFCS method plays a notable role in improving performance and mitigating challenges arising from the dynamic fluctuations in the diversity of device types within an IoT gateway's coverage zone.Computer Science, Information Systems || Engineering, Electrical & Electronic || Telecommunication

Protecting IoT Servers Against Flood Attacks with the Quasi Deterministic Transmission Policy

Servers at Supply Chains and othet Cyber-physical systems that receive packets from IoT devices should meet the QoS needs of incoming packets, and protect the system from Cyberattacks. UDP Floods are often included in attacks to overwhelm Supply Chains and the IoT through congestion that paralyzes their ability for timely Attack Detection and Mitigation. Thus this paper proposes an architecture that protects a connected Server using a Smart Quasi-Deterministic Transmission Policy Forwarder at its input. This Forwarder shapes the incoming traffic, sends it to the Server without increasing the overall packet delay, and avoids Server congestion. The relevant theoretical background is reviewed, and measurements during a UDP Flood Attack are provided to compare the Server performance, with and without the Forwarder. It is seen that during a UDP Flood Attack, the Forwarder protects the Server from congestion, allowing it to effectively identify Attack Packets. Congestion at the Forwarder is rapidly eliminated with drop commands generated by the Forwarder, or sent by the Server to the Forwarder.Computer Science, Artificial Intelligence || Computer Science, Information Systems || Computer Science, Theory & Methods || Telecommunication

Interrelationship between environmental degradation, geopolitical risk, crude oil prices, and green bonds: Evidence from the globe by sectoral analysis

By considering the motion of the world is our home, this study investigates the interrelationship between environmental degradation, geopolitical risk, crude oil prices, and green bonds across the globe. So, the research considers the probable differences between the sectors by making a detailed analysis of CO 2 emissions across sectors, applies the novel WLMC method, and uses daily data from 2nd January 2020 through 30th November 2023 for a time and frequency -based empirical analysis. The outcomes present that (i) the geopolitical risk is the most important variable on CO 2 emissions between 2020/1 and 2021/11 followed by Brent oil prices for the period 2021/12-2023/10 || (ii) green bonds are highly effective on CO 2 emissions only around 2023/11 || (iii) the impacts of the variables are quite weaker (stronger) at lower (higher) frequencies || (iv) the impacts of the variables are the same at aggregated and disaggregated levels || (v) the impact of the variables on CO 2 emissions change based on times and frequencies. Thus, the outcomes demonstrate new insights for differentiating impacts across times and frequencies, whereas the direction of the impacts is the same across aggregated and disaggregated levels. (c) 2024 International Association for Gondwana Research. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.Geosciences, Multidisciplinar

Exergoeconomic optimization of a proposed novel combined solar powered electricity and high-capacity cooling load production system for economical and potent generation via utilization of low-grade waste heat source

A novel system for combined electricity and cooling generation was introduced, integrating Flat Plate Solar Collectors (FPSC), Absorptional Heat Transformer (AHT), Organic Rankine Cycle (ORC), and Absorption Cooling Cycle (ACC) systems to utilize low-grade solar energy. The ability to use low-grade waste heat sources (70 degrees C-90 degrees C) via FPSC system for high-capacity integrated cooling and electricity generation in a more economical way, a feature not commonly addressed in conventional systems and previous literature studies, was a key advancement. The need for additional generators, boilers, and high-temperature heat sources was eliminated, resulting in substantial cost savings and a simplified system design. The FPSC-AHT integration, identified as having significant advantages over separate electricity and cooling load production, was comprehensively evaluated for its combined exergoeconomic and environmental benefits in multigeneration system design. The modeling was performed using Engineering Equation Solver (EES) and Transient System Simulation Software (TRNSYS) in Izmir, Turkey, with the aim of achieving the heightened economic efficiency and superior Coefficient of Performance (COP) values without high-temperature waste heat sources. Three configurations were examined, with the third demonstrating superior technoeconomic performance due to the increased thermal efficiency of solar hybrid photovoltaic-thermal (PV-T) systems. The higher cost per unit area in the PV-T system was effectively offset by the substantial electricity consumption, contributing to energy savings. Economic indicators for the third configuration included an initial investment of US$9.91 million, annual operational costs of US$1.29 million, a payback period of 4.2 years, an annual energy cost gain of US$9.25 million, a levelized cost of cooling (LCC) of US$0.014/kWh, and an electricity cost (LCE) of US$0.015/kWh. Through exergy analysis, toluene was identified as the optimal working fluid, revealing a total exergy destruction rate of 13245.46 kW. The performance of the proposed system was tested under different operation conditions, and based on these results, a sensitivity analysis and a comparison with the real-word studies were performed. In comparison to real- world data, the proposed system exhibits superior performance metrics, especially in terms of COP and exergy efficiency values. The optimal configuration, established using single and multiobjective optimization approaches based on exergoeconomic parameters, indicated annual electricity and cooling load production of 40000 MWh and 300 GWh, respectively. The system's efficiency in producing 1000 kW of electricity power and 4000 kW of cooling load at a comparable cost to systems generating only one output was highlighted. To determine the technoeconomic performance improvement of the proposed integrated system, the optimal configuration of the novel integrated system was compared to a reference plant for similar-scaled integrated power and cooling generation (UCI Trigeneration Plant). Compared to the UCI Trigeneration Plant, the proposed system demonstrated significant improvements in technoeconomic performance. Specifically, the proposed system achieved a 164.13 % increase in annual electricity production, a 97.38 % increase in annual cooling duty, a 60.36 % reduction in initial investment, a 57 % reduction in annual operational costs, and a 47.5 % reduction in payback period. Additionally, the levelized costs of electricity and cooling were 40 % and 22.22 % lower, respectively. Significantly higher electricity and cooling output highlights the system's ability to meet demanding energy needs. Lower initial investment and operational costs, coupled with a reduced payback period, make the system financially attractive. Lower levelized costs for electricity and cooling increase the system's competitiveness and affordability. The innovative integration of technologies provides new insights into the design of multigeneration systems, setting a new benchmark for sustainable energy solutions.Thermodynamics || Energy & Fuels || Engineering, Mechanical || Mechanic

Validation of the Short Version (TLS-15) of the Triangular Love Scale (TLS-45) Across 37 Languages (OCT, 10.1007/s10508-023-02702-7, 2023)

Psychology, Clinical || Social Sciences, Interdisciplinar