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Technology gap ratio decomposition in smallholder solar saltworks in Indonesia using meta-frontier data envelopment analysis (MetaDEA)
, Available Online, May, 2024 Campina Illa Prihantini, Nuhfil Hanani, Rosihan Asmara and Syafrial PDF (416 K) |
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Abstract: The increasing population in Indonesia results in the rising demand for consumer goods, including salt. Meanwhile, salt production in Indonesia remains traditional, using direct methods by evaporating seawater in open ponds near the coast, producing a final product called “solar salt”. This process depends on sunlight, air, weather, and seasonal climate conditions. This research aims to analyze the technical, technological, and managerial disparities among traditional solar salt farming businesses operated by local communities across regions in Madura Island—the foremost solar salt-producing region in Indonesia. This study employs primary data collected through surveys conducted during the production season in 2023/2024 in three regencies in Madura: Pamekasan, Sampang, and Sumenep. The structured questionnaires captured the input and output data. Meta-frontier Data Envelopment Analysis (meta-DEA) was applied to assess the technical efficiency of conventional solar salt productions across the research regions. The efficiency analysis revealed that, with the current production methods, solar salt farmers achieved an efficiency rate of 46.98%, with an average technical efficiency of 80.83%. This result shows that the decision-making units (DMUs) can enhance their technical efficiency by 19.07%. Meanwhile, the technology gap ratio (TGR) analysis indicates that Sumenep Regency has the highest TGR value, nearing the threshold of 1, suggesting a relatively low technology gap in this regency. The meta-DEA decomposition indicates that the determinant of the average meta-technical inefficiency among solar salt farmers is the technological disparities, with average technological gap inefficiency (TGI) values surpassing managerial gap inefficiency (MGI) values. Conversely, Sumenep Regency has a larger MGI than TGI value, implying that solar salt farmers in Sumenep possess lower managerial decision-making skills than in other regions. The findings suggest the need to enhance the adoption of the latest production technology innovations to address technological gaps in the research locations. DOI: 10.5267/j.dsl.2024.5.003 Keywords: Smallholder Solar Saltworks, Inefficiency Decomposition, Data Envelopment Analysis, Meta-frontier DEA, Technical Efficiency, Indonesia
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Open Access Original Article | |||
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Genetic algorithm approach to asymmetric capacitated vehicle routing: A case study on bread distribution in Istanbul, Türkiye
, Available Online, May, 2024 Büşra Meniz and Fatma Tiryaki PDF (416 K) |
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Abstract: Conveying the products to the customers under optimized circumstances is as crucial for the companies as the production itself. One optimization strategy to consider is transportation with the minimum quantity of vehicles and the selection of courses with the minimum distance between the locations. In other words, it is the examination of the solution to the Vehicle Routing Problem (VRP), particularly the Capacitated VRP (CVRP), which is a more realistic modelization approach. For businesses that perform distribution to customers frequently, such as management work with the coordination of daily distribution, finishing the distribution on time is of great importance. In big cities with complicated roads and many dropping points, this can be achieved by benefiting from the systematic modeling of the CVRP. In this study, the delivery network investigation for one production facility of the Istanbul People's Bread positioned on the Asian side of Istanbul, Türkiye that distributes three times a day will be the focus of interest. The corresponding Asymmetric CVRP (ACVRP) for the facility network and 215 bread-selling buffets with authentic driving distances will be solved with the Genetic Algorithm (GA), and an optimized transportation network will be presented. DOI: 10.5267/j.dsl.2024.5.002 Keywords: Genetic algorithm, People's bread, Asymmetric capacitated vehicle routing, Optimization, Sustainability
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Exploring attitude and intention toward solar panel cleaning robots: Evidence from user insights
, Available Online, May, 2024 Rubporn Promvongsanon, Sudaporn Sawmong and Bilal Khalid PDF (416 K) |
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Abstract: There is a global trend towards adopting green energy, with solar energy being the primary source derived from solar panel technologies. Solar panels can generate enough power for general and household use. However, to effectively function and serve their purpose, they require regular cleaning and effective maintenance, and robotic cleaning is among the current applicable technologies. This research aims to determine the intention of using solar panel cleaning robots in Thailand for individual solar panel users. The study was hinged on the extended C-TAM-TPB model. The quantitative survey study design was employed using primary data collected from individual solar panel users in their households. 419 respondents were used to collect the data. The C-TAM-TPB model proposed using reliability, validity, and model fitness which employed confirmatory factor analysis (CFA). They adopted structural equation modeling (SEM) in the evaluation of the variables' relationships and study hypotheses. Subjective norms and trust in technology, individual control perception, and awareness of renewable energy significantly and positively affected behavioral intention to use solar panel cleaning robots as indicated by the study. Trust in technology, awareness of renewable energy, and environmental concerns were found to be pivotal mediators to the attitude effect on individual users' intention to act in using solar panel cleaning robots. The authors recommend that to improve the adoption of solar panel cleaning robots; the concerned stakeholders should consider, firstly, enhancing trust in the technology of these robots, which is crucial, focusing on aspects like reliability, privacy, security, and reputation. Secondly, considering the influence of subjective norms, including perceptions from family, friends, colleagues, and experts, is essential. Perceived behavioral control should also be a focal point, encompassing self-efficacy, resources, and complexity. Moreover, increasing awareness of renewable energy and environmental benefits is vital to encourage individual adoption. The research also recommended that to encourage the adoption and use of solar panel cleaning robots, the aspects that should be emphasized include subjective norm, perceived behavior control, trust in technology, and awareness of renewable energy. DOI: 10.5267/j.dsl.2024.5.001 Keywords: Cleaning Robots, Energy Efficiency, Green Energy, Renewable Energy, Solar Panel, Sustainable Technology
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Open Access Original Article | |||
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The role of top management commitment to improve operational performance through it adoption, supply chain integration, and green supply chain management
, Available Online, April, 2024 Zenia Estella Soesetyo, Zeplin Jiwa Husada Tarigan, Hotlan Siagian, Sautma Ronni Basana and Ferry Jie PDF (416 K) |
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Abstract: Manufacturing companies constantly strive to produce products that promote better competitiveness. In addition, the current business environment requires manufacturing companies to adopt environmentally friendly concepts, which have become a global customer concern. Therefore, companies must inevitably meet environmental protection requirements through ecologically friendly processes and products. Meanwhile, environmentally friendly adoption requires a capital-intensive investment, which doubts the management regarding the investment return. Hence, top management commitment is highly needed to maintain eco-friendly products and contribute to the company's performance. This study examines the role of top management commitment to operational performance through adopting information technology, supply chain integration, and green supply chain management. This study surveyed manufacturing companies that have implemented ISO 14000, as many as 73 companies with criteria of having more than 100 employees. Data is collected using questionnaires directly and online with Google Forms. The results of data processing analysis found that top management commitment influences information technology adoption with a priority scale to maintain competitiveness and strategies that increase competitiveness. Top management commitment through information technology can improve supply chain integration and green supply chain management. In addition, supply chain integration improves green supply chain management and operational performance. Implement environmental-friendly measures by involving external partners to impact operational performance. The results of this study contribute to enriching supply chain management theory by significantly adopting green supply chain management to improve sustainable development and performance. It also makes a practical contribution by providing insight for practitioners to generate added value for customers. DOI: 10.5267/j.dsl.2024.4.007 Keywords: Top management commitment, Information technology adoption, Supply chain integration, Green supply chain management, Operational performance
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Inventory model for empty container reposition problem considering quality dependent returns and port capacity constraint
, Available Online, April, 2024 Lukmandono, Anindya Rachma Dwicahyani and Zeplin Jiwa Husada Tarigan PDF (416 K) |
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Abstract: In this study, an Economic Return Quantity (ERQ) model for the Empty Container Reposition (ECR) problem using the reverse logistics (RL) approach is developed. Some of the model’s primary considerations are the return rate that depends on the quantity and quality of the empty container, and the capacity constraints to hold the empty container in the port. The model of ERQ is optimized using an analytical approach. Based on the result of the hypothetical case, the authors examined that the acceptable quality level of reusable containers should be set at 67%, 55%, and 50% for the three types of containers to be able to obtain minimum inventory costs. Two cases of binding and nonbinding constraints are investigated, and it is found that the binding constraint gives 3.4% higher cost than the latter. The results of this study help the container depots to plan, manage, and handle empty containers so that the container utility can be increased, and inventory costs can be minimized. DOI: 10.5267/j.dsl.2024.4.006 Keywords: Port logistics, Empty container repositioning, Optimization, Inventory, Lot sizing
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Open Access Original Article | |||
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Climate change and rainfall in the Pacaya Samiria National Reserve
, Available Online, April, 2024 Jessica Yasumi Solis Rafael, Rosmery Condori Islachin, Yadina Elena Moreno Millan and Dante Manuel Garcia Jimenez PDF (416 K) |
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Abstract: Rainfall and temperature are essential inputs for agricultural production, especially climate change-related ones. In turn, it is necessary for the development and survival of both men and animals at all biotic levels. In a reserve of great importance for the country, such as the Pacaya Samiria, these two factors play a preponderant role in the survival of animals and inhabitants of it. In this paper, VAR analysis with Granger's causality was used to determine the relationship between both variables. It was shown that there was a short-term positive relationship between climate change and rainfall in Pacaya Samiria. DOI: 10.5267/j.dsl.2024.4.005 Keywords: Climate change, Rainforest, Granger, Causality
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Open Access Original Article | |||
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Consumer behavior towards e-wallet usage in the post-COVID-19 era in Saudi Arabia
, Available Online, April, 2024 Fahad Alofan and Majd Almarshud PDF (416 K) |
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Abstract: Saudi Arabia's Vision 2030 seeks to transition towards a cashless society and increase non-cash transactions to 70% by 2025. The COVID-19 pandemic has further accelerated cashless activities in Saudi Arabia, with e-payments increasing by 75% in the past year. This study explores consumer behavior towards using e-wallets in the post-COVID-19 era by employing the extended Technology Acceptance Model (TAM). The results of an online survey conducted among 303 Saudi citizens were analyzed using SPSS. This study examines the correlation coefficients between the variables and conducts an ANOVA to determine the influence of all variables on consumer behavior towards e-wallets in Saudi Arabia post-COVID-19. The findings indicate that consumer behavior is positively influenced by perceived usefulness, perceived ease of use, lifestyle compatibility, and traceability, whereas cost does not significantly impact the use of e-wallets. Additionally, the results show that approximately 28.1% of the respondents used e-wallet services due to the pandemic. This study adds to the literature by expanding on previous work on the topic and providing detailed insights into the factors of e-wallet acceptability in Saudi Arabia. DOI: 10.5267/j.dsl.2024.4.004 Keywords: COVID-19 pandemic, E-payments, TAM, Quality of life, Consumer behavior, E-wallet
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Open Access Original Article | |||
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The application of improved backpropagation neural network in college student achievement prediction
, Available Online, April, 2024 Qin Qin and ShiHui Jiang PDF (416 K) |
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Abstract: Educational institutions generate a large amount of digital data in their daily operations, which is stored in servers, forming a substantial educational data set. Extracting valuable information through practical data analysis has become a critical problem that needs to be solved urgently. Students' examination results are an essential basis for evaluating their learning status, which reflects the effect of school education to some extent. Therefore, we propose a model based on the BP network and Pandas to construct a prediction model for Pandas' performance in the first year and their successful graduation to explore the potential relationship between Pandas' performance in the freshman year and graduation, thus realizing the principle of early guidance and improvement of teaching quality. Through the random prediction experiment of 9,424 scores data of 304 students in 2017 and 2018 majoring in network engineering at a university, the accuracy rate is 96.71% after the experimental data analysis and verification, which has proved that there is a potential correlation between the students' first-year course scores and graduation. Meanwhile, the improved BP network proposed in the present research exhibits reasonable practicability and extensibility in the college student achievement prediction model. DOI: 10.5267/j.dsl.2024.4.003 Keywords: BP neural network, Student achievement prediction, Pandas, Course credit, Python
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Affecting factors to the decision on digital transformation and its process at small and medium-sized enterprises in Hanoi, Vietnam
, Available Online, April, 2024 Vinh Phung The, Quy Nguyen Ngoc, Thao Truong Duc, Long Pham Tran Thang, Trang Nguyen Minh and Linh Nguyen Thuy PDF (416 K) |
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Abstract: The research was conducted based on the theory of planned behavior (TPB), with the research model built on 06 influencing factors to the digital transformation process of businesses, with the intermediate variable “Decision on digital transformation”. There were 456 small and medium-sized enterprises in Hanoi surveyed for this research from March to June 2023. Research results found that the digital transformation process of small and medium-sized businesses in Hanoi are strongly affected by the “digital transformation decision”; while the technology platform and employees' capabilities largely determine these businesses’ decision to digital transformation and its process. On that basis, three policy implications are proposed to promote the digital transformation process at small and medium-sized enterprises in Hanoi. DOI: 10.5267/j.dsl.2024.4.002 Keywords: Digital transformation, Business digital transformation, Small and medium-sized enterprises in Hanoi
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Open Access Original Article | |||
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A hybrid genetic-simulated annealing algorithm for multiple traveling salesman problems
, Available Online, April, 2024 F. Smaili PDF (416 K) |
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Abstract: The Multiple Traveling Salesman Problem (MTSP) was able to model and solve various theoretical and real-life applications. This problem is one of the many difficult issues that have no perfect solution yet. In this paper, on the one hand genetic algorithms with different combinations of operators and simulated annealing were used to solve the MTSP. On the other hand, the genetic algorithm with the combination of operators that gave the best solutions of the MTSP was hybridized with a Simulated Annealing algorithm. The simulation results showed that the hybrid algorithm significantly outperforms most of the comparable methods in obtaining the best-fitness solutions compared to the other methods in most of the test cases. In addition, by scaling the fitness function according to the amplitude of tours, it was obvious that the non-dominated front obtained by the hybrid algorithm was better than the non-dominated front obtained by the other algorithms. DOI: 10.5267/j.dsl.2024.4.001 Keywords: MTSP, Genetic algorithm, Simulated annealing, Hybrid algorithm, Non-dominated front, Statistical Analyses
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Open Access Original Article | |||
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A metaheuristic algorithm based on Ant Colony Based approach for the assigning tasks problem to a workforce with different skills
, Available Online, March, 2024 Roosvell Camilo Velandia, David Alvarez Martinez and John Willmer Escobar PDF (416 K) |
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Abstract: This paper studies the problem of assigning tasks to a workforce with different skills. The problem is modeled as an unrelated parallel scheduling problem, incorporating sequence-dependent setup times (UPMSPSDST). Exact methods generally are not able to solve real large problems of UPMSPSDST. Hence, this research introduces an efficient, straightforward metaheuristic solution leveraging the Ant Colony Optimization (ACO) algorithm. The objective is to minimize the total completion time while assigning jobs to unrelated parallel machines with sequence-dependent preparation times. The algorithm establishes a threshold for improving the Ants (solutions) to select only promising ants for the improvement phase, thereby reducing the computational effort performed by local search operators. The proposed ACO algorithm maintains a basic structure and could be extended to solve other scheduling problems. A set of test instances available in the literature has been used to validate the efficiency of the proposed methodology. In addition, the results have been compared with the best previously published works. The ACO algorithm improves 30% of the best-known solutions (BKS) and reaches 30% of the BKS. The results show that the average performance of the ACO algorithm exceeds the average performance of the methods used by the best previously published works for the UPMSPSDST. DOI: 10.5267/j.dsl.2024.3.006 Keywords: Ant Colony Optimization, Multiskill Workforce Scheduling, Unrelated Parallel Machine, Scheduling Problem
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Towards sustainable polio vaccine distribution: Evaluating a green metrics framework in Indonesia's pharmaceutical industry
, Available Online, March, 2024 Agus Purnomo and Syafrianita PDF (416 K) |
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Abstract: This study endeavors to evaluate the effectiveness of green distribution and green supply chain practices at PT Bio Farma (Persero) in relation to polio vaccine products. The ultimate objective is to establish and attain future green distribution targets. The research methodology utilizes the Green Supply Chain Operations Reference (Green SCOR) model and the Analytical Hierarchy Process (AHP) to analyze the production and distribution data of polio vaccine (OPV) and inactivated polio vaccine (IPV) products from January to December 2023. The performance values for each key component of Green Distribution and Green Supply Chain are as follows: Plan = 22.9, Source = 16.60, Make = 21.53, Deliver = 11.24, and Return = 7.08. The total performance value for Green Distribution and Green Supply Chain is 79.41. According to APICS standards, the performance of Green Distribution and Green Supply Chain is rated as “Good”. Future performance improvements will focus on supply chain and collaborative planning, establishing long-term partnerships with suppliers and customers, optimizing environmentally friendly transportation, and developing the enterprise information system. Our study proposes that the distribution and logistics managers at PT Bio Farma should persistently monitor and assess their operations to enhance the efficiency of their green distribution and green supply chains. By doing so, they can ensure the successful attainment of performance objectives for disseminating the polio vaccine in Indonesia. This research presents a significant advancement by incorporating the Green SCOR framework into the specific domain of polio vaccines, emphasizing sustainability and environmental efficiency. This approach paves the way for new avenues of investigation in green supply chain research and offers a novel viewpoint on how the pharmaceutical industry, specifically vaccine distribution, can utilize sustainable practices to enhance their operations while mitigating environmental ramifications. DOI: 10.5267/j.dsl.2024.3.005 Keywords: Analytical Hierarchy Process (AHP), Green SCOR, Green Distribution, Green Supply Chain, Polio Vaccine
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Open Access Original Article | |||
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Simple and efficient duelist algorithm variations for energy-aware virtual machine placement in cloud data centers
, Available Online, March, 2024 Amol Adamuthe and Vrushabh D. Kupwade PDF (416 K) |
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Abstract: This research presents a novel approach to address the Virtual Machine Placement Problem (VMPP) in cloud data centers with the aim of minimizing energy consumption. The main contributions of this study are threefold. Firstly, a Duelist Algorithm specifically designed for VMPP, which introduces a unique concept of duelists combined with optimization techniques. The algorithm aims to strike a balance between exploration and exploitation in the search space, leading to more effective resource allocation and energy-efficient cloud data center management. Secondly, enhance the performance of the Duelist Algorithm by reducing the number of algorithm-specific parameters. This simplifies the implementation process and increases the algorithm's adaptability to various real-world problems, making it more user-friendly and robust. Lastly, conduct a comprehensive comparison of the Duelist Algorithm with the widely used Hybrid Harmony Search Algorithm (HS+SA+LS) in terms of energy consumption and overall efficiency. The experimental results demonstrate that the Duelist Algorithm consistently outperforms the Hybrid Harmony Search Algorithm, achieving remarkable improvements in both best and mean fitness values. Additionally, the Duelist Algorithm exhibits lower standard deviation values, indicating more stable and consistent performance. The findings of this research validate the effectiveness of the proposed Duelist Algorithm in minimizing energy consumption and optimizing cloud resource allocation. The reduction of algorithm-specific parameters further contributes to its versatility and simplicity. DOI: 10.5267/j.dsl.2024.3.004 Keywords: Energy efficiency in cloud, Virtual machine placement, Duelist algorithm
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