Analyzing Degree of Parallelism for Concurrent Timed Workflow Processes With Shared Resources

Yanhua DU, Li WANG, X. LI

IEEE Transactions on Engineering Management

février 2017, vol. 64, n°1, pp.42 - 56

Départements : Information Systems and Operations Management, GREGHEC (CNRS)

Mots clés : Business, Servers, Computational modeling, Uncertainty, Analytical models, Processor scheduling, workflow management, Business process management, degree of parallelism, Petri net (PN), timed workflow net (TWF-Net)

Degree of parallelism is an important factor in workflow process management, because it is useful to accurately estimate the server costs and schedule severs in workflow processes. However, existing methods that are developed to compute degree of parallelism neglect to consider activities with uncertain execution time. In addition, these methods are limited in dealing with the situation where activities in multiple concurrent workflow processes use shared resources. To address the limitations, we propose a new approach to analyzing degree of parallelism for concurrent workflow processes with shared resources. Superior over the existing methods, our approach can compute degree of parallelism for multiple concurrent workflow processes that have activities with uncertain execution time and shared resources. Expectation degree of parallelism is useful to estimate the server costs of the workflow processes, and maximum degree of parallelism can guide managers to allocate severs or virtual machines based on the business requirement. We demonstrate the application of the approach and evaluate the effectiveness in a real-world business scenario.

Developing knowledge from entrepreneurial actions – toward a taxonomy


Journal of Small Business and Enterprise Development

2017, vol. 24, n°4, pp.793-813

Départements : Information Systems and Operations Management, GREGHEC (CNRS)

Mots clés : Experiential learning, Qualitative method, Knowledge development, Entrepreneurial learning

Purpose – The purpose of this paper is to enrich our understanding of entrepreneurs’ daily deeds, tasks and activities. The research investigates the ways in which entrepreneurs seize opportunities and gain knowledge from the start to the expansion of their ventures.Design/methodology/approach – Two case studies were developed based on a longitudinal fine-grained analysis of two ventures over two years. Entrepreneurs’ success and learning were modeled in line with grounded theory methodology. Data were collected from both primary and secondary sources in the form of semi-structured interviews and archival documentation.Findings – The authors develop an original conceptual framework that consists of ten entrepreneurial learning opportunities and four knowledge development modes. There are ten generic types of actions that entrepreneurs take. There are then four distinctive ways to transform these experiences into knowledge. The model is assessed in absolute terms and relatively to existing taxonomies.Research limitations/implications – The findings question the premises on which entrepreneurial learning research traditionally relies. Opportunities can be open-ended rather than purely instrumental. Similarly, knowledge can be emerging as much as it can be espoused. This opens-up space for further research.Practical implications – For practitioners, the findings suggest new ways for making sense of the daily experience of their entrepreneurial endeavor. The learning modes suggested can be used by coaches and mentors when helping entrepreneurs in their venture.Originality/value – The research provides empirical evidence of what entrepreneurs do. This may help cast traditional debates about what there is to do (logical necessity) and what there is to know (a priori knowledge) in a new light.

Pricing and Capacity Allocation for Shared Services


Manufacturing & Service Operations Management

printemps 2017, vol. 19, n°2, pp.230-245

Départements : Information Systems and Operations Management

Mots clés : customer mix; customer interaction; price discrimination; capacity allocation; shared services

We study the pricing and capacity allocation problem of a service provider who serves two distinct customer classes. Customers in each class are inherently heterogeneous in their willingness to pay for service, but their utilities are also affected by the presence of other customers in the system. Specifically, customer utilities depend on how many customers are in the system at the time of service as well as who these other customers are. We find that if the service provider can price discriminate between customer classes, pricing out a class, i.e., operating an exclusive system, can sometimes be optimal and depends only on classes’ perceptions of each other. If the provider must charge a single price, an exclusive system is even more likely. We extend our analysis to a service provider who can prevent class interaction by allocating separate capacity segments to the two customer classes. Under price discrimination, allocating capacity is optimal if the “net appreciation” between classes, as defined in the paper, is negative. However, under a single-price policy, allocating capacity can be optimal even if this net appreciation is positive. We describe in detail how the nature of asymmetry in classes’ perception of each other determines the optimal strategy

Topological network design of closed finite capacity supply chain networks


Journal of Manufacturing Systems

octobre 2017, vol. 45, pp.70-81

Départements : Information Systems and Operations Management

Mots clés : Closed;Finite networks;M/M/1/K;M/G/c/c;M/G/∞ queues

In this paper, we examine the layout, location, and general topological arrangement of queues in a closed finite queueing network environment for supply chains. Since our focus is on manufacturing environments, then maximizing throughput is a worthy performance measure objective. We are given a network topology G(V, E) with a finite set of nodes and edges and we wish to assign the queues to the nodes V ∈ G such a way that the maximum throughput is achieved. This is a nonlinear continuous optimization problem with implicit integer variables so the problem is at least NP-Hard. We also examine the impacts of Additive Manufacturing (AM) on the throughput of the supply chain. Decentralization of the supply chain topology as evidence by the increased dispersal of nodes within the topology tends to increase the throughput of the system, so the AM leaf nodes can have a measurable and significant impact on SCM throughput.