Journal of the Operational Research Society

Mortenson, Michael J.; Doherty, Neil F.; Robinson, Stewart

doi: 10.1080/01605682.2019.1605468pmid: N/A

AbstractIn recent years there has been a growth in specialised analytics Master’s degrees, in the UK and beyond. However, there has been little research into the contents of such degrees. In particular, the role disciplines such as operational research play within them remains an under-explored area. Using a mixed-methods approach, this article analyses UK Master’s degrees in analytics to determine a typology of provisions. Firstly, a support vector classifier is used to identify the traditional disciplines analytics degrees most closely align with. Secondly, a hybrid approach to analyse the modules included in analytics curricula is employed, as part of which a new metric (module topic weighting) is presented. The analysis identifies two main categories of degrees, the first aligning with machine learning and computing topics; the second operational research and business themes. The paper concludes by evaluating the implications this has for students, employers, educators and the operational research discipline.

Liu, Zhixin; Lu, Liang; Qi, Xiangtong

doi: 10.1080/01605682.2019.1605470pmid: N/A

AbstractBy virtue of its cost advantage, online shopping has attracted a substantial population of consumers. At the same time, lacking the first-hand touching experience in online shopping often causes a utility mismatch to consumers, which may not only turn down some potential consumers but also cause a high return rate. A recent business practice for retailers is to encourage showrooming – consumers browsing product in the offline channel but switching to the online channel for purchases, with an aim to leverage both the low cost from the online channel and the real experience from the offline channel. We address such a dual-channel system with omni channels, i.e., concurrently running a mix of online and offline channels by a joint decision on pricing for the two channels as well as the associated return policy. Using an appropriate model we show that a well-designed dual-channel system can indeed increase the profitability of a retailer. Specifically, we find that channel cost difference is the key factor behind the rationale of encouraging showrooming. Retailers can intentionally create a channel price gap to facilitate demand shifting from offline channel to online channel, thus achieving considerable fulfilment cost savings as well as return cost savings. In addition, we reveal that return policy decision is closely related with pricing decisions, and show that return policy design can be viewed as a tool for market segmentation through modulating channel prices. Finally, we identify several barriers for retailers to engage with consumers directly such as consumer valuation uncertainty and cost efficiency of handling returns, and show that it may be beneficial for retailers to engage with consumers indirectly via consumer showrooming.

Wyburn, John

doi: 10.1080/01605682.2019.1609880pmid: N/A

AbstractTypical assumptions regarding language planning applied to populations bilingual in English and in a second, minority language are realised in an epidemiological system dynamics model. These assumptions are shown to fail to consider the overwhelming and growing influence of English-language media, both passive (entertainment) and active (especially social media). This influence is subsequently modelled as an English-speaking population of high connectivity, attracting actual and potential bilinguals to effective unilingualism. The flow and loop structure of the model is demonstrated to entail long-term English language dominance. The model is applied to bilingual populations in the United Kingdom, Eire, and New Zealand. Recent trends are duplicated and projections given. Threshold values of parameters critical for survival and for the attainment of published goals are found, and current language planning criticised with reference to these.

Chen, Xin; Xu, Weijun; Liang, Haiming; Dong, Yucheng

doi: 10.1080/01605682.2019.1609888pmid: N/A

AbstractIn multi-attribute group decision-making problem (MAGDM), the existing consensus reaching process (CRP) is to obtain a consensus ranking of alternatives. However, these CRPs contradict some real-life MAGDM problems in which decision-makers do not need to rank alternatives and hope to classify the alternatives into several groups instead. Thus, in this paper we propose a new CRP in MAGDM, called the classification-based consensus reaching process (CCRP). First, we present a feedback method with minimum adjustments to generate the optimal adjusted individual matrices via a 0–1 mixed linear programming model for CCRP. Subsequently, we develop the interactive consensus reaching process based on the feedback method with minimum adjustments in CCRP. Finally, a practical example from China Undergraduate Mathematical Contest in Modeling and a simulation analysis are conducted to demonstrate the validity of the proposed CCRP.

Barkaoui, M.; Berger, J.

doi: 10.1080/01605682.2019.1609891pmid: N/A

AbstractMany heuristics and meta-heuristics problem-solving methods have been proposed so far to solve the NP-hard multi-satellite collection scheduling problem (m-SatCSP). In particular, genetic algorithms (GAs), well-suited for large scale problems, its simplicity and low cost implementation have been pervasive. However, most contributions largely emphasise simple variant or basic GA principles promotion, overlooking prior problem structure exploitation or potential problem-solving benefits that may be conveyed from similar combinatorial optimisation problems such as the vehicle routing problem with time windows (VRPTW). In fact, despite some recognised similarity with VRPTW and early investigation on limited exact methods, few efforts have been successfully reported to adapt efficient advanced special-purpose problem-solving techniques to m-SatCSP. In this paper, a VRPTW-based hybrid genetic algorithm is proposed to tackle the single objective static m-SatCSP. The advocated approach combines and adapts well-known routing heuristics knowledge with standard genetic operator principles to efficiently explore promising search regions, manage constraint handling and improve solution quality. The hybrid strategy co-evolves two populations of solution plan individuals, maximising expected collection value while concurrently densifying collection paths to minimise orbit demand. Computational results show the approach to be cost-effective and competitive in comparison to some recent methods inspired from the best reported m-SatCSP heuristics.

Choi, Kanghwa

doi: 10.1080/01605682.2019.1609886pmid: N/A

AbstractPrevious advertising efficiency studies have neglected the “black box” of the consumer purchase funnel. Thus, this study decomposes advertising efficiency into marketing and sales efficiency to unravel a complicated and multi-stage consumer purchase decision, and measures divisional advertising efficiency in the US consumer car purchase funnel using a slack-based measure network data envelopment analysis. Additionally, this study identifies consumer key brand perception attributes that affect divisional advertising efficiency by using a bootstrapped truncated regression to offer strategic advertising initiatives that are appropriate to car brand position and characteristics at each step of the customer buying funnel. The contributions of this study are twofold. First, this study is an unprecedented attempt at researching the divisional advertising efficiency for opening the hidden “black box” of the consumer car purchase journey. Second, this study suggests that advertising strategies, such as advertising themes and appeal type, should be differentiated in accordance with consumer key brand perception attributes at each step of the customer buying funnel, depending on car brand types such as luxury and mainstream.

Wang, Lin; Kunc, Martin; Li, Jianping

doi: 10.1080/01605682.2019.1609890pmid: N/A

AbstractEven though systems thinking has been highlighted in portfolio management theory, independent project control logic still dominates its implementation process. This paper constructs a system dynamics model for portfolio monitoring and control. Considering the on-going portfolio as a complex social system, the impacts of project interdependencies (PIs) on portfolio decision-making are investigated under a behavioural paradigm. Our findings indicate the remedial actions, affected by behavioural factors like planning fallacy and “Pet project” effects, may generate escalation of commitment under specific levels of uncertainty and interdependencies. Thus, portfolio coordination decisions should be made from a strategic perspective with the consideration of complexities embedded in the system and behavioural responses from portfolio managers.

Gehret, Greg H.; Weir, Jeffery D.; Johnson, Alan W.; Jacques, David R.

doi: 10.1080/01605682.2019.1610206pmid: N/A

AbstractMany firms generate revenue by operating systems or fleets, such as welding robots, rental cars, aircraft, etc. The contribution of service parts to the availability of the system or fleet is well documented. The majority of service parts are intermittently demanded. Research on intermittent demand has primarily focused on forecast accuracy and generally does not distinguish between the stock policies of consumable versus repairable parts. Often, systems and fleets contain repairable parts which are refurbished because doing so is more cost-effective for the firm than the procurement of new parts. Managing repairable parts is considerably more complex than managing consumable parts. In this article, we create a new approach to advance the supply chain manager’s ability to determine cost-effective stock policy on these intermittently-demanded, repairable service parts. We then test the new approach via a case study and show the approach to be beneficial for a given firm.

Ahmadi, Reza

doi: 10.1080/01605682.2019.1614490pmid: N/A

AbstractMaintenance policies are developed for decision-making about repair and maintenance of deteriorating parallel systems consisting identical components whose failures are detected only by inspections. Inspections at periodic times reveal the true state of components and preventive and corrective maintenance actions are carried out in response to the observed components state. The decision process is driven by the excursion of a state process regulated through an age reduction model. The modelling approach allows a wide class of models to be considered. Assuming a threshold-type policy, the article aims at minimising the long-run average maintenance cost per unit time by determining appropriate inspection intervals and a maintenance threshold. Using the renewal-reward theorem, the expected cost per cycle and expected cycle length emerge as solutions of equations, and a recursive scheme is devised to solve them. We illustrate the procedure for the case when the components’ lifetime conforms to the Weibull distribution. Furthermore, a sensitivity analysis is performed to examine the effect of model’s parameters. The unified structure developed allows different scenarios to be explored.

Campello, B. S. C.; Ghidini, C. T. L. S.; Ayres, A. O. C.; Oliveira, W. A.

doi: 10.1080/01605682.2019.1619892pmid: N/A

AbstractIn recent years, researchers have investigated a variety of approaches to integrating lot sizing and cutting stock problems due to their high importance in the manufacturing industry. Although the mono-objective integrated problem has been considered an excellent alternative for minimising global costs, it does not include all the multiple criteria involved in the manufacturing process. Thus, to address this issue, we use a multiobjective approach and explain its importance in providing various answers to the decision maker through the Pareto-optimal solution set. We analyse existing trade-offs and correlations between each cost of the integrated problem and the related decision variables. Several computational tests are performed, which validate the efficacy of our strategy.