Engineering January 2017 Practioner Learning Uncategorized

IEEE Transactions on Engineering Management Editorial for February 2017 Issue

1.Special Issues

Proposals for special issues on topics of current interest in engineering, technology, and innovation management are always welcome. Please send a brief description of the concept for the issue to me (sabherwal@ieee.org). I will circulate it to department editors, and if the initial response is favorable, I will request a specific plan and more detailed information to be used in the final decision about proceeding with the special issue.

2.Online Submission and Review System

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3.About This Issue

This issue of the IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT includes nine research articles. The relevance and usefulness of the articles are summarized below:

“A Systematic Literature Review of Constraint-Based Innovations: State of the Art and Future Perspectives” (by Agarwal, Grottke, Mishra, and Brem): This article synthesizes the existing literature on innovation approaches adopted under scarcity conditions, placing emphasis on emerging markets and bottom-of-pyramid customers. The authors conduct a systematic literature review of constraint-based innovations to explore the progress of the extant research and facilitate future work. Their findings de-emphasize the role of technology spillovers from the West and indicate growing applications of constraint-based innovations beyond emerging markets to wider markets. The paper thus provides managers with insights into resource-constrained innovations. It sheds some light on the essential product characteristics and enabling approaches through prescriptive variables. Further, the article offers interpretations on constraint-based innovations terminology such as “cost effectiveness” and “ease of use,” which can be helpful in developing products and implementing diffusion strategies.

http://ieeexplore.ieee.org/document/7782762/

“Technological Uncertainty and Firm Boundaries: The Moderating Effect of Knowledge Modularity” (by Fixson, Khachatryan, and Lee): Managers responsible for managing the development of technological innovations must continuously decide on the scope of their firms’ technical development work. This task is particularly challenging in emerging industries that typically exhibit high levels of technological uncertainty. The findings of this research can help technology and innovation managers with this task in two ways. First, the results point R&D managers to the value of understanding knowledge modularity for the decision on their firms’ R&D scopes and explains how and why knowledge modularity affects firms’ responses to technological uncertainty. Second, while knowledge modularity on the industry-level is a theoretical construct, the authors’ newly constructed measure for knowledge modularity allows practitioners to actually gauge it through the use of patent data that are publicly accessible.

http://ieeexplore.ieee.org/document/7811242/

“Engineering Management Models for Urban Security” (by Muaafa and Ramirez-Marquez): In this article, a mathematical framework is developed to support managerial challenge of identifying optimal patrolling strategies where each strategy involves specific patrolling routes for each police officer. The framework includes a multi-objective optimization model with the following goals: (1) minimize operating cost C(y), (2) minimize the cost-benefit ratio CB(y), and (3) maximize visibility V(y). A heuristic technique is developed to solve the model and obtain an approximate Pareto set of pseudo-optimal solutions. A statistical method for eliciting probabilities of crimes using the geographical and crime data for the north part of the city of Seattle is presented. Further, the solutions have been discussed with members of the police force to understand implementation issues and practicalities of patrolling under proposed solutions.

http://ieeexplore.ieee.org/document/7797517/

 “Analyzing Degree of Parallelism for Concurrent Timed Workflow Processes with Shared Resources” (by Du, Wang, and Li): In this paper, the authors propose an approach to computing two kinds of degree of parallelism for concurrent timed workflow processes with shared resources: expectation degree of parallelism (EDP) and maximum degree of parallelism (MDP). EDP refers to the expectation number of severs or virtual machines (VMs) needed by the workflow processes in parallel, which is the basis for evaluating the cost of severs or VMs during the execution of workflow processes and can help managers minimize the costs. MDP indicates the peak value of degree of parallelism which is the maximum number of severs or VMs needed by the workflow processes. If the number of severs or VMs in a firm is less than the requirement of the workflow processes, managers have to adjust the structure of workflow processes and reduce the number of severs or VMs according to MDP. In practice, the two kinds of degree of parallelism are of great importance.

http://ieeexplore.ieee.org/document/7778113/

“Information Sharing in the Supply Chains of Products with Seasonal Demand” (by Huang, Ho, and Fang): This study considers a two-echelon supply chain with seasonal consumer demand, in which the impacts of the degree of information sharing on the supplier’s profits are investigated. In considering both the benefit and cost of sharing information, information sharing can be profitable for both the supplier and retailer in the supply chain. However, continuously increasing the degree of information sharing would eventually result in a decrease in the supplier’s net profit. In fact, an excessive amount of information sharing can result in high costs for the supplier, and thus determining an optimal degree of information sharing to benefit both the supplier and retailer is essential for effective supply chain management. Proposing a way to achieve this objective is the main contribution of the study. The derived results can be applied in practice to a decentralized supply chain in any industry with seasonal demand.

http://ieeexplore.ieee.org/document/7742955/

 “Green Supply Chain Formation through By-Product Synergies” (by Sun, Sabbaghi, and Ashton): From a practical perspective, this work provides insights into how firms could benefit from recovering and reusing industrial by-products, and how the likelihood of formation of such a by-product synergy is influenced by various factors, such as the by-product trading price, the fixed cost of synergy formation, and market conditions. The paper further sheds light on incentivizing the synergy formation and its consequent environmental impact for network facilitators (e.g., Chicago Waste-to-Profit Network) whose role is to promote by-product synergy formation among firms in traditionally unrelated industries. More specifically, the authors offer insights into how firms’ share of fixed cost and the by-product trading price interact in determining the economic viability of the synergy formation. Also, they offer advice on when demand volatility plays a positive or negative role in the synergy formation. Finally, they discuss the conditions under which the environmental improvement can be maximized when forming the synergy (i.e., no waste disposal and no need for the harmful conventional input).

http://ieeexplore.ieee.org/document/7815283/

“Improving Bot-In-Time Delivery of Mobile Robotic Fulfillment Systems for Online Retailers” (by Zhe and GONG): Mobile Robotic Fulfillment System (MRFS) is a real warehousing system used in Amazon and other online retailers. Based on MRFS, a new operational mode called Bot-In-Time Delivery (by Forbes) is rapidly developing. While “the last mile problem” is one of major concerns for online retailers, MRFS can be used to achieve speedy delivery. However, in practice, it is unclear how to design capacities for minimizing the throughput time. To answer this application question, this article provides the effective support to determine optimal capacities (the number of robots and their velocities) for minimizing the throughput time, of managerial relevance to time-based competitive advantages for online retailers.

http://ieeexplore.ieee.org/document/7820133/

“Stochastic Single-Machine Scheduling with Learning Effect” (by Li): The models and theoretical results developed in this paper can assist decision-makers to obtain job sequence on a single-machine that optimizes the expected total flow time and expected makespan, while explicitly considering uncertain job processing time and/or learning rate. Details about how to construct the optimization model and implement the solution methods in practice are presented. Computational experiments offer managerial insights into how the optimal objective value is impacted by the amount of uncertainty. Practical guidance is provided on how to quantify the expected value of perfect information, as the gap between the performance of optimal policy and the deterministic solution with perfect information. http://ieeexplore.ieee.org/document/7756418/

“Measuring Modularity: Engineering and Management Effects of Different Approaches” (by Cabigiosu and Camuffo): This study shows how using different modularity measures to infer product architectural properties, and that support engineering or organizational design may be misleading. In fact, other things being equal, products and organizations may or may not seem to have “mirroring” architectural properties contingent on the applied measure. Among the most widespread measures, the authors identify the more informative and robust, which jointly captures interfaces standardization and 1:1 function-component mapping. Their findings suggest that firms put diverse emphasis over different product attributes. Hence, while technology matters, firms’ characteristics, such as their strategy, organizational structures or capabilities, may be relevant to better understand how product and organization design co-vary. Overall, the study suggests that managers use a situational approach to choosing the most appropriate modularity measure, considering the relevant technical and business constraints and opportunities.

http://ieeexplore.ieee.org/document/7737009/

About the author

Rajiv Sabherwal

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