A multi-attribute model to optimize the price and composition of prepaid mobile Internet plans

Sohrabi, Arya; Pishvaee, Mir Saman; Hafezalkotob, Ashkan; Bamdad, Shahrooz

doi:10.1108/jeim-09-2019-0279

Cited by 5 publications

(3 citation statements)

References 74 publications

(103 reference statements)

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“…Referring to Figure 3, it can be ascertained that customers view the attributes of product under consideration in terms of the amalgamation of different product attributes in which different product attributes have different associated levels of opportunity lost costs. This is consistent with theory of product characterization based on product attribute levels, where customers associate varying level of affinities corresponding to different product attributes (Sohrabi et al , 2020). In context of this research and from the consumer affinity standpoint, the attributes “movie” and “zoom” are perhaps the least and most preferred respectively.…”

Section: Resultssupporting

confidence: 90%

“…A trade-off between loss of opportunity in selling a specific attribute's products and number of same attribute's products left in the inventory. varying level of affinities corresponding to different product attributes (Sohrabi et al 2020). In context of this research and from the consumer affinity standpoint, the attributes "movie" and "zoom" are perhaps the least and most preferred respectively.…”

Section: Resultsmentioning

confidence: 89%

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Mitigating demand risk of durable goods in online retailing

Ghadge¹,

Bag²,

Goswami³

et al. 2020

IJRDM

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PurposeAn uncertain product demand in online retailing leads to loss of opportunity cost and customer dissatisfaction due to instances of product unavailability. On the other hand, when e-retailers store excessive inventory of durable goods to fulfill uncertain demand, it results in significant inventory holding and obsolescence cost. In view of such overstocking/understocking situations, this study attempts to mitigate online demand risk by exploring novel e-retailing approaches considering the trade-offs between opportunity cost/customer dissatisfaction and inventory holding/obsolescence cost.Design/methodology/approachFour e-retailing approaches are introduced to mitigate uncertain demand and minimize the economic losses to e-retailer. Using three months of purchased history data of online consumers for durable goods, four proposed approaches are tested by developing product attribute based algorithm to calculate the economic loss to the e-retailer.FindingsMixed e-retailing method of selling unavailable products from collaborative e-retail partner and alternative product's suggestion from own e-retailing method is found to be best for mitigating uncertain demand as well as limiting customer dissatisfaction.Research limitations/implicationsLimited numbers of risk factor have been considered in this study. In the future, others risk factors like fraudulent order of high demand products, long delivery time window risk, damage and return risk of popular products can be incorporated and handled to reduce the economic loss.Practical implicationsThe analysis can minimize the economic losses to an e-retailer and also can maximize the profit of collaborative e-retailing partner.Originality/valueThe study proposes a retailer to retailer collaboration approach without sharing the forecasted products' demand information.

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Section: Resultssupporting

confidence: 90%

Section: Resultsmentioning

confidence: 89%

Mitigating demand risk of durable goods in online retailing

Ghadge¹,

Bag²,

Goswami³

et al. 2020

IJRDM

View full text Add to dashboard Cite

show abstract

“…Next, Sohrabi et al (2020) propose deterministic and robust scenario-based mathematical models based on three different paradigms to determine the pricing and design of mobile Internet plans in a multi-attribute environment. Their decision criteria include maximising expected revenue, minimising the negative deviation from expected revenue and minimising the maximum regret.…”

mentioning

confidence: 99%

Guest editorial

Aktaş

Topçu

Kucukaltan

2020

JEIM

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International Society on Multiple Criteria Decision Making (MCDM) brings together academicians, professionals, researchers, students and policymakers at a bi-annual conference since 1975. MCDM 2019, one of those conferences, gathered 261 participants from five continents and 39 countries. The modern world is experiencing a shift from a production-focussed age to the information-focussed age. As the organisers of the conference believe that the information age will be followed by a decision age where MCDM will play a crucial role in using information and communication technology for making better decisions, they announced the theme of the conference as "MCDM beyond the information age". They also prepared the call for this special issue, inviting researchers across the world to submit their work supporting decision-making with multiple criteria methods.MCDM models incorporate concerns about multiple conflicting criteria into the management planning processes covering a wide variety of topics. With a vast domain of applications, multiple criteria decision models are increasingly used for supply chain decision-making. This special issue covers decision-making studies on quality in manufacturing, sustainability in supply chains, location selection and employee selection.We open the special issue with two papers on risk management. Unver et al. (2020) present a decision support system for proactive failure prevention in an automotive company. Automotive products have become increasingly complex, and the decision support system estimates risk scores for workstations using multiple attributes. Based on the analytic network process (AHP), the decision model brings together design-driven factors, processdriven factors and human-focussed factors to produce a risk index for each workstation. We expect this application to inform other similar applications of risk prevention in complex manufacturing environments.Fattahi et al. (2020) highlight the importance of risk management in various industries and focus on assessing the risk of different failure modes as well as several risk factors, such as occurrence, severity and detection. Their fuzzy-based FMEA model is tested in a case study, Kerman Steel Industries Factory, and a sensitivity analysis is further conducted to validate their results.Majd and Hobson (2020) develop an integrated decision model which evaluates provider agents with respect to reliability, unreliability, and uncertainty and proposes the most trustworthy provider agent in e-commerce multi-agent environments utilising TOPSIS method. The model is believed to enhance the fulfilment of purchasing between provider and requester agents.Shifting the focus to sustainability, Calik (2020) introduces a hybrid approach for supplier selection, incorporating sustainability criteria into the process. This three-stage hybrid approach starts with identifying main and sub-criteria, constructing a hierarchical structure and prioritising the criteria using the fuzzy AHP in the second stage. Finally, the third stage comprises...

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