Pricing strategy of cab aggregators in India

Anirvinna, C.; Deshmukh, Arun Kumar

doi:10.1057/s41272-019-00195-5

Cited by 5 publications

(5 citation statements)

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“…Through the portrayal of model functioning, a structured approach to address the issue of inaccessibility of customized information and incapability to manage risk is illustrated, that if made accessible, would result in an imperative change in the socioeconomic welfare of farmers. The theoretical implications emanating from the present study add to the body of knowledge and affirm that ADSS in the postharvest agriculture marketing context minimizes the agency problems by ensuring information symmetry (Narayanan and Raman, 2004), reduces transaction costs by not trading to speculative stockists (Minkoua Nzie et al, 2018), mitigates the risks and uncertainties (Anirvinna and Deshmukh, 2020;Despoudi et al, 2021) caused due to contingent environmental forces such volatile price spikes to a large extent, and augment the information intelligence facility by processing data from factors affecting price movement (Dubey et al, 2021;Jia et al, 2020). The seamless flow of realtime price-related information through the proposed ADSS fervently minimizes the information asymmetry and at the same time enables confidence in crop producers to make optimal strategic market decisions.…”

Section: Discussionsupporting

confidence: 59%

“…The theoretical implications emanating from the present study add to the body of knowledge and affirm that ADSS in the postharvest agriculture marketing context minimizes the agency problems by ensuring information symmetry (Narayanan and Raman, 2004), reduces transaction costs by not trading to speculative stockists (Minkoua Nzie et al. , 2018), mitigates the risks and uncertainties (Anirvinna and Deshmukh, 2020; Despoudi et al. , 2021) caused due to contingent environmental forces such volatile price spikes to a large extent, and augment the information intelligence facility by processing data from factors affecting price movement (Dubey et al.…”

Section: Discussionsupporting

confidence: 56%

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A farmer-centric agricultural decision support system for market dynamics in a volatile agricultural supply chain

Tripathi

Singh

et al. 2022

BIJ

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PurposeIn a volatile agricultural postharvest market, producers require more personalized information about market dynamics for informed decisions on the marketed surplus. However, this adaptive strategy fails to benefit them if the selection of a computational price predictive model to disseminate information on the market outlook is not efficient, and the associated risk of perishability, and storage cost factor are not assumed against the seemingly favourable market behaviour. Consequently, the decision of whether to store or sell at the time of crop harvest is a perennial dilemma to solve. With the intent of addressing this challenge for agricultural producers, the study is focused on designing an agricultural decision support system (ADSS) to suggest a favourable marketing strategy to crop producers.Design/methodology/approachThe present study is guided by an eclectic theoretical perspective from supply chain literature that included agency theory, transaction cost theory, organizational information processing theory and opportunity cost theory in revenue risk management. The paper models a structured iterative algorithmic framework that leverages the forecasting capacity of different time series and machine learning models, considering the effect of influencing factors on agricultural price movement for better forecasting predictability against market variability or dynamics. It also attempts to formulate an integrated risk management framework for effective sales planning decisions that factors in the associated costs of storage, rental and physical loss until the surplus is held for expected returns.FindingsEmpirical demonstration of the model was simulated on the dynamic markets of tomatoes, onions and potatoes in a north Indian region. The study results endorse that farmer-centric post-harvest information intelligence assists crop producers in the strategic sales planning of their produce, and also vigorously promotes that the effectiveness of decision making is contingent upon the selection of the best predictive model for every future market event.Practical implicationsAs a policy implication, the proposed ADSS addresses the pressing need for a robust marketing support system for the socio-economic welfare of farming communities grappling with distress sales, and low remunerative returns.Originality/valueBased on the extant literature studied, there is no such study that pays personalized attention to agricultural producers, enabling them to make a profitable sales decision against the volatile post-harvest market scenario. The present research is an attempt to fill that gap with the scope of addressing crop producer's ubiquitous dilemma of whether to sell or store at the time of harvesting. Besides, an eclectic and iterative style of predictive modelling has also a limited implication in the agricultural supply chain based on the literature; however, it is found to be a more efficient practice to function in a dynamic market outlook.

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Section: Discussionsupporting

confidence: 59%

Section: Discussionsupporting

confidence: 56%

A farmer-centric agricultural decision support system for market dynamics in a volatile agricultural supply chain

Tripathi

Singh

et al. 2022

BIJ

Self Cite

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“…Cab aggregation companies connected taxi operators or drivers with a large number of customers by giving them better chances for effectively utilising their otherwise depreciating asset. Using web based and mobile based technology, aggregators improved the driver's chances of plying more trips per day (Anirvinna and Deshmukh, 2019). On the other hand customers were assured of competitive rates and accurate billing , enhanced safety since cabs can be tracked real-time and driver identity is known.…”

Section: Background Of Can Aggregation Platform Modelmentioning

confidence: 99%

Business Model Challenges for Cab Aggregators: A Case Study of Ola

Singh¹

2020

Preprint

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This research discusses the business model challenges faced by cag aggregator platform models in developing countries. Technology-based platforms have been disrupting traditional businesses and rewriting the rules of the game. Ola cabs has been instrumental in shaping the Indian platform business landscape in a big way. Using case methodology the author analyses the situation and business model to present the salient features of Ola’s model. However, this paper also puts the spotlight on the inherent challenges in this model and warns the need for continuous business model innovation and service quality.

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“…The Indian market has witnessed an unprecedented growth of app-based cab aggregators (ABCAs) since 2010 (Anirvinna and Deshmukh, 2020;Shah et al, 2020). The present ABCA market in India consists of two major players and other minor players in limited cities, and the total market size is expected to reach USD 55,294 million by 2025 (Statista, 2021).…”

Section: Introductionmentioning

confidence: 99%

“…The Indian market has witnessed an unprecedented growth of app-based cab aggregators (ABCAs) since 2010 (Anirvinna and Deshmukh, 2020; Shah et al. , 2020).…”

Section: Introductionmentioning

confidence: 99%

Challenges in creating egalitarian logistic ecosystem: cases of app-based cab aggregators (ABCAs)

Mehta

Sharma

Chavan

2022

IJOEM

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PurposeGiven the increasing volatility, uncertainty, complexity, and ambiguity, egalitarian ecosystems may play an important role to establish equality among various stakeholders. With this idea, the study aimed to understand conflicts and challenges in creating an egalitarian ecosystem in the application-based cab aggregator (ABCA) market.Design/methodology/approachNarratives of various stakeholders involved in the ABCA business were collected. The study involved narrations from direct and indirect stakeholders up to saturation till common themes were found. Grounded theory methodology using constant comparison was explored to interpret the results. After the results were obtained, root cause analysis was undertaken using the why–why methodology to understand ground-level reality.FindingsIn total, 13 major issues were identified using grounded theory for narrative analysis that cab aggregator companies, driver-partners, and riders faced. The stakeholders' inability in the ecosystem to see each other's problems could be accorded to their self-interest, rational boundedness and asymmetric information. These findings collude with Banaji et al. (2004) and Chugh et al. (2005).Originality/valueThis study explained each stakeholder's perspectives about their counterparts that influence non-egalitarianism. The study further suggested possible areas for solving the issues and promoting cooperation.

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Pricing strategy of cab aggregators in India

Cited by 5 publications

References 4 publications

A farmer-centric agricultural decision support system for market dynamics in a volatile agricultural supply chain

A farmer-centric agricultural decision support system for market dynamics in a volatile agricultural supply chain

Business Model Challenges for Cab Aggregators: A Case Study of Ola

Challenges in creating egalitarian logistic ecosystem: cases of app-based cab aggregators (ABCAs)

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