Heavy cycles in k-connected weighted graphs with large weighted degree sums

AbstractA weighted graph is one in which every edge e is assigned a nonnegative number w(e), called the weight of e. The weight of a cycle is defined as the sum of the weights of its edges. The weighted degree of a vertex is the sum of the weights of the edges incident with it. In this paper, we prove that: Let G be a k-connected weighted graph with k⩾2. Then G contains either a Hamilton cycle or a cycle of weight at least 2m/(k+1), if G satisfies the following conditions: (1) The weighted degree sum of any k+1 pairwise nonadjacent vertices is at least m; (2) In each induced claw and each induced modified claw of G, all edges have the same weight. This generalizes an early result of Enomoto et al. on the existence of heavy cycles in k-connected weighted graphs

Lower Bounds and Semi On-line Multiprocessor Scheduling

We are given a set of identical machines and a sequence of jobs from which we know the sum of the job weights in advance. The jobs have to be assigned on-line to one of the machines and the objective is to minimize the makespan. An algorithm with performance ratio 1.6 and a lower bound of 1.5 is presented. This improves recent results by Azar and Regev who published an algorithm with performance ratio 1.625 for the less general problem that the optimal makespan is known in advance

The Bright Side of Being Uncertain: The Impact of Economic Policy Uncertainty on Corporate Innovation

Purpose: This study aims to theoretically hypothesize and empirically examine the impact of economic policy uncertainty (EPU) on firms' innovation performance as well as the contingency conditions of this relationship. Design/methodology/approach: This study collects and combines secondary longitudinal data from multiple sources to test for a direct impact of EPU on firms' innovation performance. It further examines the moderating effects of firms' operational and marketing capabilities. A series of robustness checks are performed to ensure the consistency of the findings. Findings: In contrast to the common belief that EPU reduces the innovativeness of firms, the authors find an inverted-U relationship between EPU and innovation performance, indicating that a moderate level of EPU actually promotes innovation. Further analysis suggests that firms' operational and marketing capabilities make the inverted-U relationship steeper, further enhancing firms' innovation performance at a moderate level of EPU. Originality/value: This study adds to the emerging literature that investigates the operational implications of EPU, which enhances our understanding of the potential bright side of EPU and broadens the scope of operational risk management.</p

Batch Scheduling of Deteriorating Products

In this paper we consider the problem of scheduling N jobs on a single machine, where the jobs are processed in batches and the processing time of each job is a simple linear increasing function depending on job’s waiting time, which is the time between the start of the processing of the batch to which the job belongs and the start of the processing of the job. Each batch starts from the setup time S. Jobs which are assigned to the batch are being prepared for the processing during time S0 &lt; S. After this preparation they are ready to be processed one by one. The non-negative number bi is associated with job i. The processing time of the i-th job is equal to bi(si − (sib + S0)), where sib and si are the starting time of the b-th batch to which the i-th job belongs and the starting time of this job, respectively. The objective is to minimize the completion time of the last job. We show that the problem is NP-hard. After that we present an O(N) time algorithm solving the problem optimally for the case bi = b. We further present an O(N2) time approximation algorithm with a performance guarantee 2

The impact of firms’ social media initiatives on operational efficiency and innovativeness

Social media have been increasingly adopted for organizational purposes but their operational implications are not well understood. Firms’ social media initiatives might facilitate information flow and knowledge sharing within and across organizations, strengthening firm‐customer interaction, and improving internal and external collaboration. In this research we empirically examine the impact of social media initiatives on firms’ operational efficiency and innovativeness. Taking the resource‐based view of firms’ information capability, we consider firms’ social media initiatives as strategic resources for operational improvement. We posit that firms’ social media initiatives enhance dynamic knowledge‐sharing routines through an information‐rich social network, leading to both operational efficiency and innovativeness. Collecting secondary data in a longitudinal setting from multiple sources, we construct dynamic panel data (DPD) models. Based on system generalized method of moments (GMM) estimation, we show that firms’ social media initiatives improve operational efficiency and innovativeness. We identify the importance of an information‐rich social network to the creation of knowledge‐based advantage through firms’ social media initiatives, and discuss the theoretical and managerial implications from the perspective of operations management

Global management of quality assurance systems/ Willborn

xii, 376 hal.: ill.; 24 cm

Global management of quality assurance systems/ Willborn

xii, 376 hal.: ill.; 24 cm