Jie Gao

Firms often follow the stage-gate process to manage multiple projects in product development and delegate stages of idea discovery and product development to project managers. This framework challenges the firm in designing efficient investment schemes and compensation contracts for the managers due to information asymmetry and resource conflicts among the projects. To address these challenges, we develop a principal-agent model by considering two projects in the presence of asymmetric idea quality information and unobservable development effort. Our results reveal that to incentivize the managers to report truthful idea quality and exert proper development effort, the firm should terminate low-quality ideas even though these ideas can bring positive returns with proper investment. Moreover, as the idea quality decreases, the firm should provide a fixed-salary contract rather than an outcome-based one. The asymmetric idea quality information can create under-investment inefficiency, and unobservable efforts can exacerbate this inefficiency. We further provide conditions under which encouraging resource competition among parallel projects helps alleviate the under-investment issue. Overall, our results provide guidelines for designing investment schemes and compensation contracts for parallel R&D projects in the presence of moral hazard and adverse selection and shed light on managing the resource competition to improve investment efficiency.

Information security issues have triggered both academic and practical circles to think about operation management and the sustainable development of information systems. Based on the theory of framing effect, this study constructs a theoretical model of the presentation framework of security notice information on users’ compliance willingness and empirically tests the proposed research hypotheses using a combination of behavioral experiments and questionnaires to analyze the mechanism of the information presentation framework on compliance willingness. The results show that (1) the information presentation framework has a significant effect on users’ decision to comply, but it varies according to specific frameworks. While the attribute and risk frameworks have a significant effect on users’ decision to comply, the goal framework does not have a significant effect on users’ decision to comply. (2) The security notice situation moderates the relationship between the security notice information presentation frame and users’ compliance willingness, but this varies according to the specific situation of the specific framework. The security notice situation moderates the relationship between the attribute framework, the risk framework, and users’ compliance willingness but not the relationship between the goal framework and users’ compliance willingness. (3) Information security cognition has a moderating effect on the relationship between the security notice presentation framework and users’ compliance willingness, but it varies by the specific frameworks. Information security cognition moderates the relationship between attribute frames, risk frames, and users’ compliance willingness but not the relationship between goal frames and users’ compliance willingness.

Employee security compliance behavior has become an important safeguard to protect the security of corporate information assets. Focusing on human factors, this paper discusses how to regulate and guide employees’ compliance with information security systems through effective methods. Based on protection motivation theory (PMT), a model of employees’ intention to comply with the information security system was constructed. A questionnaire survey was adopted to obtain 224 valid data points, and SPSS 26.0 was applied to verify the hypotheses underlying the research model. Then, based on the results of a regression analysis, fuzzy set qualitative comparative analysis (fsQCA) was used to explore the conditional configurations that affect employees’ intention to comply with the information security system from a holistic perspective. The empirical results demonstrated that perceived severity, perceived vulnerability, response efficacy, and self-efficacy all positively influenced the employees’ intention to comply with the information security system; while rewards and response costs had a negative effect. Threat appraisal had a greater effect on employees’ intention to comply with the information security system compared to response appraisal. The fsQCA results showed that individual antecedent conditions are not necessary to influence employees’ intention to comply with an information security system. Seven pathways exist that influence an employees’ intention to comply with an information security system, with reward, self-efficacy, and response cost being the core conditions having the highest probability of occurring in each configuration of pathways, and with perceived severity and self-efficacy appearing in the core conditions of configurations with an original coverage greater than 40%. Theoretically, this study discusses the influence of the elements of PMT on employees’ intention to comply with an information security system, reveals the mechanism of influence of the combination of the influencing factors on the outcome variables, and identifies the core factors and auxiliary factors in the condition configurations, providing a new broader perspective for the study of information security compliance behavior and providing some theoretical support for strengthening enterprise security management. Practically, targeted suggestions are proposed based on the research results, to increase the intention of enterprise employees to comply with information security systems, thereby improving the effectiveness of enterprise information security management and the degree of information security in enterprises.

Multi-center location of pharmaceutical logistics is the focus of pharmaceutical logistics research, and the dynamic uncertainty of pharmaceutical logistics multi-center location is a difficult point of research. In order to reduce the risk and cost of multi-enterprise, multi-category, large-volume, high-efficiency, and nationwide centralized medicine distribution, this study explores the best solution for planning medicine delivery for the medicine logistics. In this paper, based on the idea of big data, comprehensive consideration is given to uncertainties in center location, medicine type, medicine chemical characteristics, cost of medicine quality control (refrigeration and monitoring costs), delivery timeliness, and other factors. On this basis, a multi-center location- and route-optimization model for a medicine logistics company under dynamic uncertainty is constructed. The accuracy of the algorithm is improved by hybridizing the fuzzy C-means algorithm, sequential quadratic programming algorithm, and variable neighborhood search algorithm to combine the advantages of each. Finally, the model and the algorithm are verified through multi-enterprise, multi-category, high-volume, high-efficiency, and nationwide centralized medicine distribution cases, and various combinations of the three algorithms and several rival algorithms are compared and analyzed. Compared with rival algorithms, this hybrid algorithm has higher accuracy in solving multi-center location path optimization problem under the dynamic uncertainty in pharmaceutical logistics.

Coal gangue, an industrial waste, is rich in silicon and aluminum phase and may be used as a mineral admixture in concrete after moderately stimulating activity, allowing for efficient solid waste utilization. This study used a mortar strength and activity evaluation method to investigate single or compound activation methods to find the optimum activation method of coal gangue. FLIR, XRD, and SEM were used to investigate the activation mechanism of different modes, providing a theoretical foundation for the study of coal gangue as a concrete admixture. Results showed that mechanical ball milling, microwave, and chemical activator could activate coal gangue, and the composite activation effect was the best. The fineness of the coal gangue powder was more than 300 mesh, according to the optimal compounding method. Accordingly, the particle surface was smooth, the internal defects were reduced, and the microwave irradiation temperature was 700°C–800°C, causing the coal gangue particles to form a bonding surface and gradually agglutinate and densify. Meanwhile, the layered structure of kaolin minerals was destroyed, and a significant amount of glassy active SiO₂ and Al₂O₃ was produced, enhancing the gel ability and activity of coal gangue. Finally, 8% Ca(OH)₂ was added in the production of mortar specimens, which increased the alkalinity of the slurry, stimulated the rapid cracking and secondary hydration of the coal gangue, and enhanced the strength of mortar. At this time, the activity rate of coal gangue powder reached the highest, which was 90.5%.

This study deals with the balancing problem of a manual mixed-model assembly line, where the production volume or the product mix changes from shift to shift during the planning horizon. The unstable demand can be characterised by several representative scenarios, and the line uses overtime work to meet the demand variation. The balancing problem concerns how to assign assembly tasks to stations and determine the amount of overtime in each possible demand scenario. The objective is to satisfy the demand in each possible scenario with the minimum labour costs paid for both normal shifts and overtime work. A lower bound on the labour costs is proposed, and a heuristic algorithm is developed to quickly find a feasible solution. A branch, bound and remember (BB&R) algorithm is then proposed to find better solutions. These solution methods are tested on 765 instances. The BB&R algorithm obtains optimal solutions for 510 instances and gives high-quality solutions for the remaining 255 instances within 60 s. The experimental results show that the use of overtime work and adjustable cycle times significantly reduces the labour costs, especially when the demand or task processing time variations are large.