Showing papers in "IEEE Transactions on Engineering Management in 2016"
TL;DR: This paper surveys the DSM literature, primarily from archival journals, and organizes the developments pertaining to building, displaying, analyzing, and applying product, process, and organization DSMs, as well as recent developments with domain mappingMatrices (DMMs) and multidomain matrices (MDMs).
Abstract: The design structure matrix (DSM), also called the dependency structure matrix, has become a widely used modeling framework across many areas of research and practice. The DSM brings advantages of simplicity and conciseness in representation, and, supported by appropriate analysis, can also highlight important patterns in system architectures (design structures), such as modules and cycles. A literature review in 2001 cited about 100 DSM papers; there have been over 1000 since. Thus, it is useful to survey the latest DSM extensions and innovations to help consolidate progress and identify promising opportunities for further research. This paper surveys the DSM literature, primarily from archival journals, and organizes the developments pertaining to building, displaying, analyzing, and applying product, process, and organization DSMs. It then addresses DSM applications in other domains, as well as recent developments with domain mapping matrices (DMMs) and multidomain matrices (MDMs). Overall, DSM methods are becoming more mainstream, especially in the areas of engineering design, engineering management, management/organization science, and systems engineering. Despite significant research contributions, however, DSM awareness seems to be spreading more slowly in the realm of project management.
254 citations
TL;DR: It is concluded that manufacturing industries can benefit more from green process innovation by leveraging their internal absorptive capability, as opposed to replying on external government subsidies as commonly believed.
Abstract: Being “green” is socially, desirable, yet whether it pays to be “green” is unclear. This question has become more important to manufacturing industries as environmental concerns are escalating, particularly in emerging economies. We examine the effects of green process innovation on the financial performance of manufacturing industries with a focus on the moderating effects of government subsidies versus industries' own absorptive capability. Using sulfur dioxide emissions as an environmental index, we establish a dynamic model using ten years panel data from 28 industries in China where environmental concerns have been severe and government subsidies have been commonly believed to be instrumental. The results show that clean technologies and end-of-pipe technologies are positively related to financial performance at the industry level, thus it pays to be “green.” Furthermore, strong absorptive capacity tends to enhance this relationship, but surprisingly green subsidies turn out to weaken this relationship. We also find the effects are different between clean technologies and end-of-pile technologies, which leads to finer grained insights into these two types of technologies and their adoption. We conclude that manufacturing industries can benefit more from green process innovation by leveraging their internal absorptive capability, as opposed to replying on external government subsidies as commonly believed. Our findings provide finer grained insights on the benefits of green process innovation, and shed light on the study of green process innovation in other emerging economies.
140 citations
TL;DR: It is shown that the OEM may find it detrimental to offer a trade-in program when faced with competition from a 3PR, and that offering aTrade-In program may also lead to lower total environmental impact, but only in the presence of remanufactured products.
Abstract: We investigate when and how an original equipment manufacturer (OEM) should offer a trade-in rebate to recover used products in order to achieve better price discrimination and weaken competition from third-party remanufacturers (3PRs). This paper is motivated by a major IT equipment OEM, which negotiates with customers to offer them personalized trade-in rebates to induce them to return their old products and purchase new units. The company also faces increasing competition from 3PRs. We model such a trade-in program with negotiated rebates through a generalized Nash bargaining framework. Our main research question is whether the OEM should compete with a 3PR using only a trade-in program or by offering remanufactured products, or through both options. In the absence of 3PRs, the OEM always prefers to offer the trade-in program compared with not offering a trade-in program. As a trade-in program also helps to restrict the supply of used products to 3PRs, one would expect that offering a trade-in program would be more attractive in the presence of a 3PR. We show, however, that the OEM may find it detrimental to offer a trade-in program when faced with competition from a 3PR. We also show that despite the fact that cores are readily available via the trade-ins, the trade-in program makes it less attractive for the OEM to remanufacture. Finally, we show that offering a trade-in program may also lead to lower total environmental impact, but only in the presence of remanufactured products.
99 citations
TL;DR: It is suggested that a cost-effective bricolage strategy can underpin emerging market companies' development of discontinuity-creating and market disrupting technology products.
Abstract: Product innovation strategies of emerging market companies are increasingly challenging conventional wisdom. Drawing on a qualitative case study of Mahindra Reva, the only electric vehicle producer in India, this paper explores how a bricolage strategy enabled a resource-constrained emerging market firm to deliver affordable, innovative, and high-tech products with minimal capital investments. The findings of this study illustrate how multiple forms of bricolage can be implemented and managed at organizational and interorganizational levels. They show how different bricolage activities relate to different stages of the new product development process, and further, highlight the complementarities between bricolage and engineering activities. This paper argues that bricolage, which is typically regarded as a behavioral trait or skill that allows entrepreneurs and innovators to operate in challenging environments, can also be a carefully planned and executed strategy conducive to innovation. Thus, it suggests that a cost-effective bricolage strategy can underpin emerging market companies' development of discontinuity-creating and market disrupting technology products.
49 citations
TL;DR: The results reveal the different moderating roles of political ties and business ties in changing the organizational learning-innovation link, an indirect mechanism through which managerial ties affect the long-term development of firms in emerging economies.
Abstract: Although organizational learning has been recognized as an important driver of radical innovation, the literature ignores the moderating roles of managerial ties in changing the effects of learning on radical innovation. By providing access to external resources, managerial ties increase resource availability in emerging economies. Firms in these economies can utilize different ties to acquire the complementary resources for organizational learning to improve radical innovation. This study advances research on organizational learning and managerial ties by examining how different managerial ties affect the relationships between organizational learning and radical innovation in emerging economies. By integrating organizational learning theory and social capital theory, we find that political ties strengthen the relationship between exploitative learning and radical innovation, while business ties strengthen the effects of both exploratory learning and exploitative learning on radical innovation. Both types of ties strengthen the relationship between the interaction of the two types of learning and radical innovation. Our results reveal the different moderating roles of political ties and business ties in changing the organizational learning–innovation link, an indirect mechanism through which managerial ties affect the long-term development of firms in emerging economies. Firms in these economies should build the appropriate ties according to their portfolios of learning.
48 citations
TL;DR: This paper examines the platform concept and its evolution, proposes a thematic classification, and highlights emerging trends in the literature, and identifies trends and emerging themes to be addressed in future studies.
Abstract: Platforms have been considered as a paradigm for managing new product development and innovation. Since their introduction, studies on platforms have introduced multiple conceptualizations, leading to a fragmentation of research and different perspectives. By systematically reviewing the platform literature and combining bibliometric and content analyses, this paper examines the platform concept and its evolution, proposes a thematic classification, and highlights emerging trends in the literature. Based on this hybrid methodological approach (bibliometric and content analyses), the results show that platform research has primarily focused on issues that are mainly related to firms’ internal aspects, such as innovation, modularity, commonality, and mass customization. Moreover, scholars have recently started to focus on new research themes, including managerial questions related to capability building, strategy, and ecosystem building based on platforms. As its main contributions, this paper improves the understanding of and clarifies the evolutionary trajectory of the platform concept, and identifies trends and emerging themes to be addressed in future studies.
47 citations
TL;DR: A theory-driven empirical model is developed that integrates the core concepts of supply chain risk management and information processing theory to generate research findings with theoretical and managerial implications and suggests that except for product complexity, all the other posited product-specific and environment-related uncertainty characteristics positively moderate the relationship between supply chainrisk information capability and operational performance.
Abstract: To mitigate and respond to supply chain risks, previous research usually views supply chain risk management as the management of various activities concerning risk identification, assessment, mitigation, and responses. While supply chain risk information plays a crucial role in the implementation and decisions of many of these activities, the importance of a firm's information processing capability to its supply chain risk management effort has received very little attention in the literature. Using information processing theory as the theoretical lens, we argue that a firm's capability in processing supply chain risk information, which comprises supply chain risk information sharing and supply chain risk information analysis, can improve operational performance, and this capability's effectiveness in improving performance is contingent on product-specific uncertainty characteristics (i.e., product complexity and product customization) and environment-related uncertainty characteristics (i.e., technology turbulence and market turbulence). We test the proposed theoretical model using data collected from 350 manufacturing firms in China. The results support that supply chain risk information processing capability comprises two constituent elements and has a positive effect on operational performance. The results also suggest that except for product complexity, all the other posited product-specific and environment-related uncertainty characteristics positively moderate the relationship between supply chain risk information capability and operational performance. We contribute to the literature by developing a theory-driven empirical model that integrates the core concepts of supply chain risk management and information processing theory to generate research findings with theoretical and managerial implications.
44 citations
TL;DR: Using survey data on 261 firms in technology-intensive industries in China, this study shows an inverse U-shaped relationship between external KH and innovation performance, indicating that internal and external KH have varying influences on innovation performance.
Abstract: Heterogeneous knowledge sources may have decreasing returns for innovation performance. While scholars have widely examined the effect of knowledge heterogeneity (KH) on innovation performance, little has been done to explore the differences between external and internal KH, and to integrate these two sources of KH. This study examines the independent and combined effects (the multiplicative and balanced effects) of internal and external KH on innovation performance. Using survey data on 261 firms in technology-intensive industries in China, our study shows an inverse U-shaped relationship between external KH and innovation performance. This differs from the relationship between internal KH and innovation performance, which has a linear rather than curvilinear effect, indicating that internal and external KH have varying influences on innovation performance. By combining the two effects, we find that both the complementary and balanced effects of internal and external KH on innovation performance are significant and positive. The findings indicate that managers should not only put an emphasis on developing internal and external KH, but also identify the means to combine the two types of KH to increase innovation performance.
38 citations
TL;DR: It is shown that promotion focus interacts with the work and family environments to predict academic scientists' entrepreneurial intentions, and the vital role of the environment in encouraging academic entrepreneurship is highlighted.
Abstract: Using a sample of academic scientists, we show that promotion focus interacts with the work and family environments to predict academic scientists’ entrepreneurial intentions. Concretely, we find that the relationship between promotion focus and entrepreneurial intentions is particularly strong when scientists’ parents have owned a business and when they work in laboratories with more industry-financed research. As such, our study complements prior research into entrepreneurial intentions in academia, which has to a large extent focused on individual characteristics as determinants of such intentions. We highlight the vital role of the environment in encouraging academic entrepreneurship. Without a supportive environment, high promotion focus individuals are unlikely to become entrepreneurs. Our study has implications for the entrepreneurship literature, in particular academic entrepreneurship, and we call for more research on the individual–environment nexus.
32 citations
TL;DR: This work proposes a two-stage DSS that will assist managers in not only select mitigation strategies for supply chain risks, but also mitigation tactics when risks occur, and employs a novel matrix formulation for decision-tree analysis, which integrates expert judgments.
Abstract: Decision support systems (DSSs) for supply chain risk management benefit from a holistic approach for mitigating risks, which include identification and assessment of risks and evaluation and selection of measures to appease risks. However, previous studies in this area overlooked probability estimation, measure selection, and assessment of interdependence of risks and measures. We aim to fill these gaps in the literature by proposing a two-stage DSSs that will assist managers in not only select mitigation strategies for supply chain risks, but also mitigation tactics when risks occur. Our DSS employs a novel matrix formulation for decision-tree analysis, which integrates expert judgments. We applied our models to the supply chain of a fast-expanding offshore-wind industry, which faces high levels of exposure to risks because of the associated complexities in this domain. The results demonstrate how to select mitigation strategies and mitigation tactics for managing supply chain risks within the offshore-wind industry.
32 citations
TL;DR: It is found that project managers have a significantly higher level of the emotional exhaustion form of burnout than other job classifications and construction project personnel suffer from a significantlyHigher level of emotional exhaustion than those working on other classes of project.
Abstract: As a result of the frenetic and demanding working conditions associated with projects, much research and theory has addressed the stress and burn-out propensity of members of project teams. However, research has generally not taken into consideration the differential effects of job title or types of project organizations on job demands, perhaps assuming that all levels within a project team and all project types offer similar levels of job demands. This study addresses the question of how the perception of job demands varies by job title (project manager, engineer, and project team member) and across project type (construction, research and development, and information technology). Using a sample of 208 project personnel, we examined the dimensions of burnout (emotional exhaustion, cynicism, and reduced personal efficacy) for the evidence of their differential impact across both job title and project type. Our findings suggest that there is no significant difference in perceived job demands across both job title and project type. However, we found that project managers have a significantly higher level of the emotional exhaustion form of burnout than other job classifications and construction project personnel suffer from a significantly higher level of emotional exhaustion than those working on other classes of project.
TL;DR: A new approach is introduced that addresses TOD via patent outlierness, leveraging both patent attributes and citations, and proposes the following characteristics for patent outliers: not highly clustered with other patents; low node centrality within the citation network; and low similarity to other patents in the network.
Abstract: Effectively ranking patents in outlierness in a patent citation network is a crucial task for patent analysis, including as it relates to technological opportunity discovery (TOD). Previous studies in the area of TOD focus on patent textual data. In this paper, we introduce a new approach that addresses TOD via patent outlierness, leveraging both patent attributes and citations. We propose the following characteristics for patent outliers: 1) not highly clustered with other patents; 2) low node centrality within the citation network; and 3) low similarity to other patents in the network. Existing outlier ranking approaches have the drawback of not leveraging the unique characteristics of attributed patent citation networks. We propose new outlier ranking methods developed specifically for patents in attributed patent citation networks. Attribute data independently describe a patent, while citation network data relate patents to each other, thus capturing patent outlierness from two different aspects. The contributions of this paper are, given an attributed patent citation network: 1) patent clustering algorithm, and 2) method for scoring and ranking patents in outlierness. Developed methods are validated using artificial datasets. Proposed outlier ranking methods are evaluated using U.S. patents in the area of digital information and security.
TL;DR: It is demonstrated that R can offer a menu of two RQDs to M, however, Pareto improvement is not always guaranteed by using RQD, and the foundation to advance knowledge on how channel leadership affects performance under both the information symmetric and asymmetric cases is laid.
Abstract: This paper studies the effects of channel leadership and information asymmetry on supply chain coordination (SCC) of a single-manufacturer ( M ) single-retailer ( R ) supply chain, which sells a product with a general stochastic price-dependent-demand function. Three all-units quantity discount (QD) contracts are examined: 1) the manufacturer-led QD (MQD); 2) the retailer-led QD (RQD); and 3) the vendor managed inventory QD (VQD), which represent different channel leaderships. The problems are constructed as multistage sequential games. We find that any VQD that coordinates the supply chain has an equivalent RQD counterpart, and hence only MQD and RQD need to be examined for SCC. For the symmetric information scenario, both MQD and RQD can achieve coordination and the respective conditions for RQD are distribution free, but not for the MQD case. Only RQD, but not MQD, can always achieve Pareto improvement. For the asymmetric information scenario, MQD achieves coordination only if the actual supply chain's optimal quantity is known by M , but this condition is not needed for RQD. There is a unique RQD that achieves SCC, and hence the profit division between channel members is fixed. To overcome this inflexibility issue, we demonstrate that R can offer a menu of two RQDs to M . However, Pareto improvement is not always guaranteed by using RQD. Since QD contracts are widely adopted in practice, this paper lays the foundation to advance our knowledge on how channel leadership affects performance under both the information symmetric and asymmetric cases.
TL;DR: A hybrid evolutionary algorithm that combines nondominated sorting genetic algorithm II (NSGA-II) with a local search method to solve the NP-hard problem with biobjective for the multiperiod design problem of a reverse logistics network for repair service is proposed.
Abstract: In recent years, the ever-rising return streams for repair service have forced the electronics manufacturers to expand their reverse logistics capacities. However, most existing papers on the reverse logistics network design neglected the time sensitivity of the return flows. Moreover, most of these investigations were primarily concerned with the single objective problems of either minimizing the total cost or maximizing the profit. In this paper, we propose a biobjective mixed-integer linear programming model for the multiperiod design problem of a reverse logistics network for repair service. A multiperiod setting is taken into account to make the reverse logistics network flexible to accommodate the gradual changes in the capacity of the facilities and the network configuration. To solve the NP-hard problem with biobjective, we develop a hybrid evolutionary algorithm that combines nondominated sorting genetic algorithm II (NSGA-II) with a local search method. We compare the hybrid evolutionary algorithm with NSGA-II and ϵ-constraint method using numerical examples. The comparison results indicate that the hybrid evolutionary algorithm outperforms the NSGA-II in most cases. The ϵ-constraint method performs best for the small instances, but it cannot solve large instances within reasonable time. Finally, an extensive parametric analysis is conducted and several managerial insights are derived.
TL;DR: It is elemental for organizations to be aware of this phenomenon and configure their risk management processes accordingly based on the dependences among the various risks to which the organizations are exposed.
Abstract: This paper investigates the factors behind silo-based risk management practices in organizations. Based on interviews with different actors working with the supply management processes within and across different organizational levels in a major multinational manufacturing corporation, it reveals how silos of risk management activities are formed. The findings show that there are profound differences in risk visibility between different actors due to differences in their hierarchical levels, organizational positions, and business contexts. Drawing on the theoretical lenses of bounded rationality and contingency theory, the paper reveals how these differences in visibility create silo-based risk management processes and discusses the pros and cons of such configurations. It concludes that silo-based behaviors are inherent features of any complex organization and that the implications of managing risks in silos are strongly influenced by the types of dependences (positive or negative) among risks. Therefore, it is elemental for organizations to be aware of this phenomenon and configure their risk management processes accordingly based on the dependences among the various risks to which the organizations are exposed.
TL;DR: A new method to estimate the process capability, and a new criterion for capability and performance assessment based on kernel function and fuzzy analysis hierarchy process (FAHP), which can improve the adaptation of process capability analysis.
Abstract: Because of more and more complexity of an operation environment in today's industrial production process, it is difficult to monitor the process operation quality and to estimate the performance efficiency based on the existing mathematical model and knowledge. This paper proposes a new method to estimate the process capability, and a new criterion for capability and performance assessment. This method is based on kernel function and fuzzy analysis hierarchy process (FAHP), which can improve the adaptation of process capability analysis. The device process capability can be estimated by FAHP with main variables, which are determined by interpretive structure modeling. The estimators of these indices overcome uncertainties caused by data fluctuation in the traditional process capability, and could strongly improve the robustness and adaptability of the process capability estimation and diagnosis. The proposed methods are used in a simulation of the Tennessee Eastman process. The results demonstrate the efficiency and validity of the presented approach. The proposed method can provide more performance decision information of industrial process to help decision makers evaluate and diagnose the state of the production devices, and improve the process operations.
TL;DR: This study examines how firms' innovation strategies rely on different knowledge sources (own-generated, bought-in, and codeveloped) that affect innovation performance using data from the 2008 Community Innovation Survey, and finds that firms that simultaneously pursue both exploration and exploitation will have maximal innovation performance by investing into all three types of knowledge sources.
Abstract: Using an exploration–exploitation framework, this study examines how firms’ innovation strategies rely on different knowledge sources (own-generated, bought-in, and codeveloped) that affect innovation performance. It utilizes data from the 2008 Community Innovation Survey covering 9054 sample firms from 14 European countries. Results derived from multiple-method empirical analysis indicate that investments into acquiring different knowledge sources will generate different values, depending on key contextual factors. In particular, we find that for firms following explorative innovation strategy (focused on developing new products, processes, and technologies), investments in own-generated and bought-in knowledge will improve innovation performance, whereas for those following exploitative innovation strategy (focused on refining existing products, processes and technologies), only investments in bought-in knowledge will create a positive impact on innovation performance. Additionally, firms that simultaneously pursue both exploration and exploitation (ambidextrous innovation strategy) will have maximal innovation performance by investing into all three types of knowledge sources. This study hence contributes new insights regarding the strategic choice of knowledge source.
TL;DR: It is shown that the choice of the level of centralization of product design decisions should be made contingent to the product complexity and behavioral factors of project managers involved in the decisions.
Abstract: In practice, product design decisions in a buyer–supplier setting can be either centralized or decentralized. Yet, it is unclear in what circumstances either of these settings can result in higher new product performance. In this study, we show that the choice of the level of centralization of product design decisions should be made contingent to the product complexity and behavioral factors of project managers involved in the decisions. In particular, we examine the influence of the cognitive ability, resistance to change, and cognitive effort of the project managers on the choice of the level of centralization of product design decisions. A methodology coming from complexity science is adopted and a simulation analysis is carried out. Results confirm that product complexity affects the relationship between the level of centralization of the product design decisions and product performance. Furthermore, we show that the benefit of centralized product design decisions is influenced by the level of cognitive effort, cognitive ability, and resistance to change of project managers. The analysis is performed in two different contexts characterized by varying levels of trust between the buyer and supplier. We discuss the implications of our findings for theory and practice.
TL;DR: An incentive compatible mechanism based on real option analysis to suggest which project stage to best engage the supplier is proposed and provides managerial insights into how to best balance the time-to-market mandate with the need for accruing significant innovations through supply chain partnerships.
Abstract: Early supplier involvement (ESI) infuses upfront supplier resources and expertise to accelerate the research and development (R&D) timeline, and allow for risk sharing. Successful implementation of ESI in a new product development setting, however, remains elusive due to the intricacy of interfirm collaboration while dealing with unproven technology and market uncertainty. Extending from prior ESI studies on supplier selection, resource integration, and relationship management, we propose game theoretical contracting strategies to achieve manufacturer objectives, such as predictable design timelines, sufficient supplier commitment, and radical in-process innovations. Taking into account various project factors, such as revenue forecast, technical uncertainty, market competition, and team capability, we propose an incentive compatible mechanism based on real option analysis to suggest which project stage to best engage the supplier. The supplier, in turn, can follow our analysis to determine whether to participate, and if so, the appropriate level of resource commitment. The equilibrium analysis provides managerial insights into how to best balance the time-to-market mandate with the need for accruing significant innovations through supply chain partnerships.
TL;DR: This paper extends the analysis of supplier development investments to a triadic setting where a second buying firm also invests in the development of a supplier, and is able to make novel predictions about the buyers' behavior in supply chains.
Abstract: This paper extends the analysis of supplier development investments to a triadic setting where a second buying firm also invests in the development of a supplier. The analysis of buying firms’ cost-based decision of the optimal supplier development investment shows that noncooperation between the two buying firms leads to higher total development investments than cooperation. Hence, the decision to cooperate with other buyers in development activities reduces total development investments. Within this triadic setting, we are able to make novel predictions about the buyers’ behavior in supply chains.
TL;DR: A mean-risk optimization model for the long-term risk management problem of an energy consumer using stochastic programming is developed and it is demonstrated that on-site generation affects the consumer's decision to purchase financial hedges.
Abstract: The adoption of small-scale electricity generation has been hindered by uncertain electricity and gas prices. In order to overcome this barrier to investment, we develop a mean-risk optimization model for the long-term risk management problem of an energy consumer using stochastic programming. The consumer can invest in a number of generation technologies, and also has access to electricity and gas futures to reduce its risk. We examine the role of on-site generation in the consumer's risk management strategy, as well as interactions between on-site generation and financial hedges. Our study shows that by swapping electricity (with high price volatility) for gas (with low price volatility), even relatively inefficient technologies reduce risk exposure and CO $_2$ emissions. The capability of on-site generation is enhanced through the use of combined heat and power (CHP) applications. In essence, by investing in a CHP unit, a consumer obtains the option to use on-site generation whenever the electricity price peaks, thereby reducing its financial risk. Finally, in contrast to the extant literature, we demonstrate that on-site generation affects the consumer's decision to purchase financial hedges. In particular, while on-site generation and electricity futures may act as substitutes, on-site generation and gas futures can function as complements.
TL;DR: A discrete stress-strength interference (DSSI) theory-based dynamic supplier selection model is presented for maintenance service outsourcing process and can help users outsource the corresponding maintenance service to the most suitable supplier at different periods.
Abstract: Maintenance service outsourcing is a strategic driver for asset intensive industries pursuing the enhancement of supply chain performance. Maintenance service supplier selection plays a relevant role in this premise since its significant impact on equipment availability, and hence, on business success. To periodically review suppliers’ performances and update the outsourcing contract, a discrete stress–strength interference (DSSI) theory-based dynamic supplier selection model is presented for maintenance service outsourcing process. Taken account of the influence of randomness and uncertainty, a novel and universal evaluation criterion, demand fulfillment level (DFL) is introduced based on the DSSI theory. DFL is relevant to two random variables, which are random user's service order quantity (stress) and random supplier's service fulfillment quantity (strength), and DFL is defined as the probability that the latter (strength) is larger than the former (stress). Based on DFL, the proposed model can help users outsource the corresponding maintenance service to the most suitable supplier (maximum supplier reliability) at different periods. The decision rule can be described as a dynamic 3-D diagram, according to which decision makers can periodically review suppliers’ performances and update the outsourcing contract. A case study on maintenance service supplier selection problem for a steel company illustrates the effectiveness of the proposed model.
TL;DR: A general safety-stock determination approach under nonstationary stochastic demand and random supply yield is developed, and a considerable service improvement and inventory decrease of the safety- stock approach is demonstrated.
Abstract: Nonstationary stochastic demand and random supply yield have led to a great challenge in construction material management. Appropriate safety stocks can cope with uncertainty in both demand and supply yield, and improve the construction cost and productivity significantly. But the safety stock is usually determined by planner's experience or rough evaluation in management practice, which results in overstock or understock situations frequently. For changing this situation, this paper focuses on analysis of the stochastic inventory control problem of construction material, and develops a general safety-stock determination approach under nonstationary stochastic demand and random supply yield. Based on the linear-order release rule and modified base-stock definition, the inventory balance equation is developed. Then, a coverage random variable, which incorporates the complete information of outstanding orders, is defined to represent the outflows and inflows to stock over risk periods. Meanwhile, the fixed-point iteration method is adopted to calculate the time-varying safety-stock level under predefined service-level (nonstockout probability) constraint. Finally, a numerical analysis is conducted to investigate the relative performance of the proposed safety-stock approach and days of supply rule. The result demonstrates a considerable service improvement and inventory decrease of the safety-stock approach.
TL;DR: Results show that user representatives played a pivotal role as they used a variety of mechanisms for crossing physical boundaries, cognitive boundaries, and social boundaries as well as creating a common knowledge space, shared knowledge, and knowledge adaptation.
Abstract: Cross boundary knowledge management (KM) is essential for the successful implementation of enterprise systems (ES), and user representatives undertake a critical role in the process. However, this important phenomenon has been largely overlooked by the extant literature. Drawing upon cross boundary KM theories and the ES implementation literature, this exploratory case study investigates how user representatives facilitate cross boundary KM and what mechanisms are used to be effective. The implementation of ES by Alpha (pseudonym) was examined because it involved a wide range of organizational units and stakeholders, which made cross boundary knowledge flow difficult. Results show that user representatives played a pivotal role as they used a variety of mechanisms for crossing physical boundaries, cognitive boundaries, and social boundaries. A process model was developed to reveal how boundary-crossing mechanisms affect KM via creating a common knowledge space, shared knowledge, and knowledge adaptation. This study makes three theoretical contributions. It develops an integrated model for understanding the cross boundary mechanisms by user representatives, extends prior research on cross boundary KM from a vendor perspective only to a client perspective, and it broadens research on user participation with the ES implementation context. This research also has significant implications for practitioners such as user representatives, project managers, and consultants.
TL;DR: An optimization model is presented that extends previous approaches focused on optimizing production plans to the JIT setting and, based on real order release information provided to the supplier, two simple adjustment heuristic methods are developed.
Abstract: This paper considers an auto parts supplier who receives order release updates from its customers and revises its production plan for future periods on a weekly basis. The inaccuracy of the order releases causes significant costs in the form of premium expedited transportation, production overtime, and excess inventory. This setting provides a rich context for studying order release variance, because the supply chain has adopted a just-in-time (JIT) approach where ideal inventory levels are kept at zero. This leads to a high reliance on order release accuracy in order to manage production quantities. This paper presents an optimization model that extends previous approaches focused on optimizing production plans to the JIT setting. Furthermore, based on real order release information provided to the supplier, two simple adjustment heuristic methods are developed. The performances of these approaches are compared with relying solely on order releases received from the customers. The simple median-based adjustment heuristic performs the best of all the approaches. Implications of the analysis are also discussed.
TL;DR: A bilevel programming model is proposed and a benders decomposition algorithm is developed for small-size problems and two bileVEL metaheuristics are suggested to solve this Stachelberg interdictor-evader game for large- size problems.
Abstract: The vehicle routing problem is one of the most important and well-known issues that is considered by researchers in recent years. There are some vital or expensive shipments, such as fuel shipments, vehicles carrying money, prisoner transfer vehicles, and so on, that are being assassinated by some interdictors. The problem of routing in these kinds of shipments is more complicated in comparison with the classical routing problems. In this paper, routing of these special kinds of shipments is integrated for the first time into the network interdiction concepts. For this purpose, a bilevel programming model is proposed and a benders decomposition algorithm is developed for small-size problems. Two super-valid inequalities are proposed to improve the efficiency of this algorithm. Also, two bilevel metaheuristics are suggested to solve this Stachelberg interdictor-evader game for large-size problems. To show the applicability and efficiency of the solution methods, some randomly generated and also benchmark instances are used. The computational results show that the two proposed metaheuristic algorithms could be effective for solving these problems.
TL;DR: The model, which extends the multimode resource-constrained project scheduling problem by including value, generates an efficient frontier that includes the best project plans for varying project costs.
Abstract: The current trend in modern project management methodologies is to maximize project values. We suggest a quantitative model that balances time, cost, and value. It generates detailed project plans, which are feasible with respect to time, cost, and resource-constraints, and considers interactions between technical performance, time, and cost. Such interactions, which existing project management models typically ignore or project managers deal with intuitively, are important for increasing projects' values. The model, which extends the multimode resource-constrained project scheduling problem by including value, generates an efficient frontier that includes the best project plans for varying project costs. We provide illustrative examples to demonstrate the suggested approach.
TL;DR: This study examines two variants of VC, one focusing on knowledge sharing and another on support/advocacy, and shows that different dimensions of social identity matters for the two VCs, and suggests that a VC-dependent strategy with differential emphasis on developing different VC artifacts could be more fruitful.
Abstract: A fundamental issue confronting virtual community (VC) managers is how to retain the existing members and promote their continuance in the VC. Being a virtual interaction space in which members are not formally bound to stay, the extent to which members have a sense of social identity, or perceiving themselves as a part of the VC, may be a key to determine their continuance intention in the VC. However, it is important to recognize that social identity is neither a unidimensional concept nor are VCs universal in nature. In this study, we examine two variants of VCs, one focusing on knowledge sharing and another on support/advocacy, and show that different dimensions of social identity matters for the two VCs. In particular, members' sense of cognitive social identity promotes their continuance intention in knowledge-based VCs, whereas it is the emotional social identity that works in support/advocacy VCs. Furthermore, the cultivation of the two dimensions of social identity requires the facilitation of different VC artifacts. Overall, our findings offer a more nuanced understanding of the role of social identity in promoting members' continuance in VCs, and underscore that a naive universal approach of cultivating social identity without considering VC type is not enough; rather, a VC-dependent strategy with differential emphasis on developing different VC artifacts could be more fruitful.
TL;DR: It is shown that the optimal strategy prescribes simultaneous procurement from both contract and spot market sources, and the applications of the model on illustrative datasets provide insights into the relative advantages of integrating the two sources of procurement over a “pure contract” or a ”pure market” procurement source.
Abstract: We study the problem of optimally integrating contractual and spot market procurement sources for a risk-averse buying firm that purchases a commodity product at a specified rate over time. The sources involve deterministic and stochastic price processes, respectively. The risk-averse firm is concerned about the magnitude and uncertainty of procurement expenses. The problem is of increasing significance with the emergence of electronic markets that facilitate procurement from competitive spot (open) market. Models are developed to determine the optimal procurement policy in continuous time across the two sources for specified price and risk aversion parameters. We examine cases when the contract price parameter is exogenously specified and when it is endogenously adjusted according to the procurement policy. We show that the optimal strategy prescribes simultaneous procurement from both contract and spot market sources. The applications of the model on illustrative datasets provide insights into the relative advantages of integrating the two sources of procurement over a “pure contract” or a “pure market” procurement source.
TL;DR: The effectiveness of the proposed approaches for vulnerability assessment provides guides for improvement of system performances based on the trends of variations in the vulnerability grades and the dominating criterion identified for each component.
Abstract: Water supply systems around the world are becoming increasingly vulnerable as a consequence of rising climate instability and the systems' intrinsic complexity. Assessing the vulnerability of such systems is the primary and fundamental step for mitigating the negative impacts of environmental incidents. There are two main challenges in this context. First, since water supply systems are coupled with human-environment systems, the corresponding vulnerability assessment requires consideration of a host of multidimensional criteria in terms of the structures and management. Second, due to the uncertain and dynamic nature of environmental incidents, available information is not sufficient for experts to make accurate real-time judgments for the weights of criteria. To the best of our knowledge, few weight calculation approaches are able to deal with both uncertainties and subjectivities of experts' judgments under varied scenarios of the incident. These problems are solved by developing new assessment approaches consisting of four steps: 1) developing an analytical network process (ANP) criteria framework; 2) proposing a weight calculation approach by integrating game cross evaluation with stochastic ANP based on the proposed criteria framework; 3) calculating the weighted vulnerability values, rating and visualizing the vulnerability grades accordingly; and 4) performing assessment simulations and sensitivity analysis for possible scenarios. A case study of the Shanghai water supply system demonstrates the effectiveness of the proposed approaches, which provides guides for improvement of system performances based on the trends of variations in the vulnerability grades and the dominating criterion identified for each component.