Scheduling jobs with agreeable processing times and due dates on a single batch processing machine

AbstractIn this paper we study the problems of scheduling jobs with agreeable processing times and due dates on a single batch processing machine to minimize total tardiness, and weighted number of tardy jobs. We prove that the problem of minimizing total tardiness is NP-hard even if the machine capacity is two jobs and we develop a pseudo-polynomial-time algorithm for an NP-hard special case of this problem. We also develop a pseudo-polynomial-time algorithm for the NP-hard problem of minimizing weighted number of tardy jobs, which suggests that this problem cannot be strongly NP-hard unless P=NP

Customer heterogeneity in operational e-service design attributes: n empirical investigation of service quality

Purpose – This study aims to empirically examine whether heterogeneity in personal customer profiles translates to heterogeneity in the valued operational e-service design attributes. It focuses on a key operational e-service design attribute – service quality – by investigating whether customers with different profiles (demographics, pattern of use of the service, and pattern of channel use) attach different levels of importance to different dimensions of web site quality. Design/methodology/approach – The study is based on path analysis of data collected from multiple sources in a commercial e-service setting (e-banking): data from an online survey of the customers of the e-service; data stored in the transaction and log files generated by the operation of the e-service over time; and data from the e-service provider’s customer database and back office IT systems. Findings – The results suggest that: customer demographics, pattern of service use, and pattern of channel use have no influence on the importance attached by customers to web site quality dimensions; and customer demographics affect the pattern of use of an e-service. Research limitations/implications – Future research should examine this question in other types of e-services and should examine other types of profile variables. Practical implications – Service providers may not need to employ customization at the level of web site quality dimensions. The findings support the existence of the concept of an “optimal” web site design for quality. Originality/value – The paper answers calls for an increased understanding of the design of high quality e-services and for multidisciplinary research in the field of services management, in particular, incorporating operations management perspectives

Big data analytics and application for logistics and supply chain management

This special issue explores big data analytics and applications for logistics and supply chain management by examining novel methods, practices, and opportunities. The articles present and analyse a variety of opportunities to improve big data analytics and applications for logistics and supply chain management, such as those through exploring technology-driven tracking strategies, financial performance relations with data driven supply chains, and implementation issues and supply chain capability maturity with big data. This editorial note summarizes the discussions on the big data attributes, on effective practices for implementation, and on evaluation and implementation methods

A Dual-Process Model to Assess User Attitudes and the Likelihood of Electronic Word-Of-Mouth Adoption

The likelihood of electronic word-of-mouth (e-WOM) adoption is useful for academics and practitioners to understand the persuasion. To address this issue, the attitude-intention link was often assumed in information systems (IS) literature without further examinations in the persuasion contexts. This study develops a theoretical model, grounded in the elaboration likelihood model (ELM), to assess how recipients use central and peripheral routes to elaborate e-WOM. This study tests the theoretical model by surveying 395 users with viewing or posting experience in an online discussion forum. The empirical results of this study verify that the central variable (argument quality) directly and indirectly drives the likelihood of e-WOM adoption via cognitive and affective attitudes, whereas the peripheral cue (source credibility) directly and indirectly drives the likelihood of e-WOM adoption via cognitive attitudes only. However, affective attitudes rather than cognitive attitudes significantly determine the likelihood of e-WOM adoption, implying the attitude-intention link is valid in the central route to persuasion. Additionally, the use of central and peripheral routes to form attitudes is influenced by perceived control in online searching. This study also contributes to verify that argument quality acts as the diagnostic input, whereas source credibility acts as the accessible input in the elaboration of e-WOM

Optimal sequencing of a set of positive numbers with the variance of the sequence's partial sums maximized

We consider the problem of sequencing a set of positive numbers. We try to find the optimal sequence to maximize the variance of its partial sums. The optimal sequence is shown to have a beautiful structure. It is interesting to note that the symmetric problem which aims at minimizing the variance of the same partial sums is proved to be NP-complete in the literature.Comment: 12 pages;Accepted for publication in Optimization Lette

A Novel Approach to the Common Due-Date Problem on Single and Parallel Machines

This paper presents a novel idea for the general case of the Common Due-Date (CDD) scheduling problem. The problem is about scheduling a certain number of jobs on a single or parallel machines where all the jobs possess different processing times but a common due-date. The objective of the problem is to minimize the total penalty incurred due to earliness or tardiness of the job completions. This work presents exact polynomial algorithms for optimizing a given job sequence for single and identical parallel machines with the run-time complexities of $O(n \log n)$ for both cases, where $n$ is the number of jobs. Besides, we show that our approach for the parallel machine case is also suitable for non-identical parallel machines. We prove the optimality for the single machine case and the runtime complexities of both. Henceforth, we extend our approach to one particular dynamic case of the CDD and conclude the chapter with our results for the benchmark instances provided in the OR-library.Comment: Book Chapter 22 page

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

Online Makespan Minimization with Parallel Schedules

In online makespan minimization a sequence of jobs $\sigma = J_1,..., J_n$ has to be scheduled on $m$ identical parallel machines so as to minimize the maximum completion time of any job. We investigate the problem with an essentially new model of resource augmentation. Here, an online algorithm is allowed to build several schedules in parallel while processing $\sigma$. At the end of the scheduling process the best schedule is selected. This model can be viewed as providing an online algorithm with extra space, which is invested to maintain multiple solutions. The setting is of particular interest in parallel processing environments where each processor can maintain a single or a small set of solutions. We develop a (4/3+\eps)-competitive algorithm, for any 0<\eps\leq 1, that uses a number of 1/\eps^{O(\log (1/\eps))} schedules. We also give a (1+\eps)-competitive algorithm, for any 0<\eps\leq 1, that builds a polynomial number of (m/\eps)^{O(\log (1/\eps) / \eps)} schedules. This value depends on $m$ but is independent of the input $\sigma$. The performance guarantees are nearly best possible. We show that any algorithm that achieves a competitiveness smaller than 4/3 must construct $\Omega(m)$ schedules. Our algorithms make use of novel guessing schemes that (1) predict the optimum makespan of a job sequence $\sigma$ to within a factor of 1+\eps and (2) guess the job processing times and their frequencies in $\sigma$. In (2) we have to sparsify the universe of all guesses so as to reduce the number of schedules to a constant. The competitive ratios achieved using parallel schedules are considerably smaller than those in the standard problem without resource augmentation