This study investigates whether perception of product quality positively mediates the relationship between interactivity and purchase intention and whether the relationship between interactivity and perception of product quality is moderated by cost such that higher-priced items strengthen the relationship. Differences between those consumers purchasing personally or as a business were considered. Three hundred and forty-nine participants experienced a simulated environment within a real-world retail website they had previously shopped at. Results from a questionnaire were analysed using moderated mediation regression analysis. The hypothesized theoretical model was supported for individual consumers with results indicating that the effect of interactivity on purchase intention is mediated by product quality, and this indirect effect is moderated by cost. No such result was found for business consumers. This research demonstrates a notable difference between purchasing behaviours of business and individual consumers when considering interactivity and perception of product quality.

The Project Management Office (PMO) has different roles, but if it is concluded that the existence of this PMO will be needed by the project. Factors contributing to project performance include support from the PMO. PMO at PT. XYZ will begin to be implemented starting in 2019. From 2019 to 2022 work on 3 project assignments from the local government. In practice, there were problems where 2 of the three projects experienced delays in completion and 1 other project experienced payment delays, where the risks to the project have not been optimally managed. This study aims to identify the role of the project management office (PMO) owned by PT. XYZ, identify risks in PMO management and identify the role of PMO that has the most influence on risk-based project performance at PT. XYZ. The research method used in this study is a survey method for several respondents where the previous questionnaire was validated by experts and a pilot survey was carried out and the results of the questionnaire will be analyzed using the SEM method. This is to be able to provide results if risk control in PMO management is carried out effectively or on target so that it can improve project performance at PT. XYZ.

The paper aims to analyze the Technical Efficiency of 70 Commercial banks from 19 African countries from 2009-2020. Using the Data Envelopment Analysis (DEA) method of the two main approaches, Variable Return to Scale (VRS) and Constant Return to Scale (CRS) technique on a Panel Data. We find that African banks have a higher efficacy assessment with the VRS than the CRS technique, thus, with a Pure Technical Efficiency (PTE) score than Technical Efficiency (TE) . Our findings show that the majority of the banks are operating at very low levels of efficiency (not technically efficient), and inability to optimize the conversion of bank assets and liabilities into loan production for customers. Furthermore, the banks are operating inefficiently in scale, economic, and allocative manner due to mismatches in scale of production. Considering these findings, the implications of these inefficiencies extend to the overall economic development and financial stability of the region.

Carriers providing truckload freight delivery services can find value in having visibility into future demand for their services to deliver shipments (a.k.a. loads). In the extant literature, the predicted value of this visibility is improved profitability for carriers. We extend this literature by showing that profit is not the only criterion for assessing this visibility (termed future load visibility (FLV) herein). Through extensive computational experiments, we model the effects of FLV on carrier profits as well as on three other criteria that matter to other stakeholders in freight transport ecosystems: (i) ecological consequences of freight transport; (ii) customer service for freight consignors/consignees; (iii) prices that consignors pay for freight delivery. In addition to providing a multi-criteria analysis of FLV, another major novelty of our work is in showing that the level of inter-carrier competition factors into how FLV affects the various criteria. A particularly significant insight from our investigation of situations involving such competition is the seemingly paradoxical finding that carriers’ FLV possession can sometimes impede better outcomes on non-profit criteria. This and other findings yield the paper’s central conclusion that while the decision to acquire FLV is more evidently justified on the profit criterion, it is not an unequivocally optimal decision when non-profit criteria are considered.

With the development of a new generation of information technology, smart elderly care plays an important role in promoting the construction of elderly care services. The emerging application tools provide door-to-door meal service for urban elderly groups, solving meal problems for special and ordinary elderly with different priority levels and penalty costs of violating time windows. Based on this, considering the personalized needs of the elderly group, this study examines the route optimization problem of cooperative delivery of elderly meals by trucks and robots, and builds a mixed integer programming model to minimize the total cost of the system. For large-scale problems, this study designs an improved adaptive large neighbourhood search algorithm that incorporates simulated annealing algorithm and artificial bee colony algorithm to avoid falling into local optimality. Experiments have proved feasibility and effectiveness of the algorithm and proposed the corresponding management insights from the aspects of delivery efficiency and service quality.

Here, we consider the generalized travelling salesman problem (GTSP), which is a generalization of the travelling salesman problem (TSP). This problem has several real-life applications. Since the problem is complex and NP-hard, solving this problem by exact methods is very difficult. Therefore, researchers have applied several heuristic algorithms to solve this problem. We propose the application of genetic algorithms (GAs) to obtain a solution. In the GA, three operators—selection, crossover, and mutation—are successively applied to a group of chromosomes to obtain a solution to an optimization problem. The crossover operator is applied to create better offspring and thus to converge the population, and the mutation operator is applied to explore the areas that cannot be explored by the crossover operator and thus to diversify the search space. All the crossover and mutation operators developed for the TSP can be used for the GTSP with some modifications. A better combination of these two operators can create a very good GA to obtain optimal solutions to the GTSP instances. Therefore, four crossover and three mutation operators are used here to develop GAs for solving the GTSP. Then, GAs is compared on several benchmark GTSPLIB instances. Our experiment shows the effectiveness of the sequential constructive crossover operator combined with the insertion mutation operator for this problem.

On the production side, blockchain is being widely applied to agricultural product supply chains (APSCs), which can effectively improve circulation efficiency and reduce transportation losses. On the sales side, many companies are utilizing key opinion leaders (KOLs) to promote and sell agricultural products. The combination of the two enhances the farm-to-fork transparency of agricultural products and stimulates consumer purchases. Based on these, we construct four theoretical models to study blockchain investment and livestreaming mode strategies in the APSC. The results show that investing in blockchain always stimulates consumer purchases of agricultural products, while KOL livestreaming increases consumer purchases only when the increase-traffic power is greater than a certain threshold. There is a win-win situation where the fresh product supplier (FPS) and the e-retailer can benefit from investing in blockchain and introducing KOL livestreaming, respectively. Investing in blockchain is always beneficial for the KOL, and there is free-riding behavior in the APSC. Interestingly, the enhanced increase-traffic power within a certain interval may become a negative driving force, seriously harming the FPS. In addition, we find that investing in blockchain and introducing KOL livestreaming does not always benefit consumer surplus and social welfare, which depend on the KOL’s increase-traffic power, commission rate, and unit cost.

This paper addresses the problem of activity scheduling and operator assignment in workstations of aerospace assembly lines. The problem is modelled as a new variant of the Multi-Mode Resource Constrained Project Scheduling Problem (MRCPSP), which incorporates practical features from aerospace workstations in assembly lines. These workstations have a substantial number of activities to be scheduled within a given assembly cycle time. It introduces particularities which are not usually addressed such as considering additional workers for performing activities, different workers’ proficiency, and spatial limitations in work zones. The objective is to schedule the activities of an aerospace workstation, minimising the total labour cost, while satisfying the cycle time and the zone’s limitations. The problem is initially formulated by employing mixed-integer linear programming methods with mathematical modelling and solved using two different algorithms: an Ant Colony System (ACS) and a memetic ACS. Given the novelty of the problem presented, new sets of benchmark cases of different sizes for this problem are also proposed and solved. To assess the performance of the algorithms, the solutions for the small-sized instances are compared in terms of deviation with the results obtained by an optimisation modelling software. Further experimentation with the algorithms is carried out with medium and large instances, showing good performance and providing reasonably good results in realistic problems.

Order picking (OP) is a critical yet time-consuming and labor-intensive warehouse operation within the supply chain. In picker-to-part systems with high demand, pickers are exposed to fatigue due to the excessive repetition of picking activities, which results in high human energy expenditure. The literature indicates that energy expenditure depends on the picking activity and the worker’s attributes, such as pickers’ weight, gender, and age. Studies have shown that as the weights of individuals increase, the energy consumed for the same task increases. This study proposes a two-stage stochastic programming model that minimizes assignment and overtime costs while avoiding excessive fatigue levels for pickers by incorporating rest allowance into the picking tour time. In the first stage, the number of pickers required is decided. In the second stage, orders are assigned to pickers considering uncertain energy expenditure. The two-stage stochastic programming model is solved by the sample average approximation algorithm. Results show that both OP cost and the number of pickers required to fulfill an order increase when the picker’s weight exceeds 80kg. In allocating orders, pickers weighing less than 80kg should be assigned to orders with more items, such as those containing 4- or 5-items. Conversely, pickers weighing more than 80kg should be assigned to orders with fewer items, like those containing 2- or 3-items, to avoid fatigue side effects.

One of the primary goals of optimization approaches is to strike a balance between exploitation and exploration strategies, thereby enhancing the efficiency of the search process. To improve this balance, considerable research efforts have been directed towards refining these strategies. This paper introduces a novel exploration approach for the Black Widow Optimization (BWO) algorithm, termed Improved BWO (IBWO), aimed at achieving a robust equilibrium between global and local search strategies. The proposed approach tracks and remembers the effective research areas during the research iteration and uses them to direct the subsequent research process toward the most promising areas of the search space. Consequently, this method facilitates convergence towards optimal global solutions, leading to the generation of higher-quality solutions. To evaluate its performance, IBWO is compared with five optimization techniques, including BWO, GA, PSO, ABC, and BBO, across 39 benchmark functions. Simulation results demonstrate that IBWO consistently maintains precision in performance, achieving superior fitness values in 87.2%, 74.4%, and 69.2% of total trials across three distinct simulation settings. These outcomes underscore the efficacy of IBWO in effectively leveraging prior search space information to enhance the balance between exploitation and exploration capabilities. The proposed IBWO has broad applicability, addressing real-world optimization challenges in pilgrim crowd management and transportation during Hajj, supply chain logistics, and energy distribution optimization.