Coordination mechanism of IT service supply chain: an economic perspective

Yan, Jiang; Guo, Yanli; Schatzberg, Laurie

doi:10.1007/s12525-012-0086-2

Cited by 14 publications

(9 citation statements)

References 17 publications

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“…Sharing economy platforms greatly improve the degree and efficiency of information sharing, greatly reduce the degree of information asymmetry between providers and demanders, and greatly improve the efficiency of information searching for consumers. Secondly, the transparency of capital flows is different Yan et al, 2012;Guo et al, 2013). Compared with traditional economic models, platform-based business models make the flow of revenue sharing transparent, Such that those who provide services via sharing economy platforms can easily access information on order volume and demand changes.…”

Section: Methodsmentioning

confidence: 99%

Sharing Economy Platforms’ Pricing Strategies and Decision Preferences: The Example of DiDi

Guo¹,

Chen²,

Zhou³

et al. 2020

OJBM

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The sharing economy model is a new trend in the development of the Internet economy and has been widely applied in transportation industry, showing an increase in its popularity. The proliferation of the sharing economy's application prompts an investigation of its mechanisms and implications. Using DiDi, a car-sharing company, as an example, and a revenue sharing model built for the study, this paper analyzes the main factors influencing the pricing strategy choices and the decision-making behaviors of sharing economy platforms, then analyzes the factors influencing the risk of resource and customer loss. The following conclusions are drawn: First, when faced with different optimal price choices to ensure revenue maximization for platform only, versus both the platform and the providers, pricing decision of sharing economy platform is related to the sharing costs of providers and the price elasticity of expected transaction volumes. Second, a sharing economy platform tends to choose a low price strategy when the user scale (or number of users) does not exceed the scale threshold (user base), which represents the positive feedback point; otherwise, it involves high price strategies. Third, the decision preferences of a sharing platform will vary according to different marketing stages. The contributions reveal that the price-setting decisions of platform are influenced by sharing costs of providers, user scale and price elasticity.

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Section: Methodsmentioning

confidence: 99%

Sharing Economy Platforms’ Pricing Strategies and Decision Preferences: The Example of DiDi

Guo¹,

Chen²,

Zhou³

et al. 2020

OJBM

Self Cite

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“…They have found dynamic interactions between collaborative technology categories, relationship quality, resource complementarity, and performance. Yan et al (2012) applied the revenue-sharing contract theory to study the information technology (IT) SSC coordination mechanism which is usually used under the software as a service (SaaS) model and also the executive agent model. Their analysis showed that the SaaS supply chain has the optimal IT service price which is only related to the variable costs of the SaaS platform operator, so there will be perfect coordination if the variable cost can be reduced to zero.…”

Section: Literature Reviewmentioning

confidence: 99%

Exploratory Research on the Relationship Between Digital Service Supply Chain Capability and Supply Chain Performance

Ji¹

2022

EUrASEANs

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Cross-border e-commerce (CBEC) has developed rapidly in the recent years, with continuous formation of new patterns in international and domestic double cycle development in the post-epidemic era. CBEC will be playing a more important role and undertake the task of foreign trade transformation and driving domestic economic growth. In this case, the corresponding service supplies chain capability（SSCC）becomes a key part of whether the CBEC platform could complete the task. Based on the grounded theory, this research has collected data through interviews with the relevant people working in the supply chain department of the CBEC platform to systematically explore the key factors behind dynamic service capability of the digital supply chain within the CBEC platform service ability. Then, the author constructs the theoretical model of the Digital Service Supply Chain Capability. The results show that the CBEC digital service supply chain capability consists of the logistics, capital flows and information flows. Data analysis includes internal data and external data, while internal data consists of the three main categories — customer demand forecast, product quality prediction and internal data collection & analysis. Finally, external data consists of the three main categories: market intelligence collection, assessing supplier risks and big data.

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“…In the future, enterprise software shall be improved by means of decentralized mechanisms such as web‐based collaboration applications (Mourtzis, 2011; Chengalur‐Smith et al , 2012) or software agents dedicated to supply chain event management (Bearzotti et al , 2012). New business models like software‐as‐a‐service (SaaS) have been recently introduced in order to keep upfront investment small (Yan et al , 2012).…”

Section: Literature Reviewmentioning

confidence: 99%

Evaluating alternative industrial network organizations and information systems

Mittermayer

Rodríguez‐Monroy²

2013

Industrial Management &Amp; Data Systems

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PurposeThe purpose of this paper is to present a simulation‐based evaluation method for the comparison of different organizational forms and software support levels in the field of supply chain management (SCM).Design/methodology/approachApart from widely known logistic performance indicators, the discrete event simulation model considers explicitly coordination cost as stemming from iterative administration procedures.FindingsThe method is applied to an exemplary supply chain configuration considering various parameter settings. Curiously, additional coordination cost does not always result in improved logistic performance. Influence factor variations lead to different organizational recommendations. The results confirm the high importance of (up to now) disregarded dimensions when evaluating SCM concepts and IT tools.Research limitations/implicationsThe model is based on simplified product and network structures. Future research shall include more complex, real world configurations.Practical implicationsThe developed method is designed for the identification of improvement potential when SCM software is employed. Coordination schemes based only on ERP systems are valid alternatives in industrial practice because significant investment IT can be avoided. Therefore, the evaluation of these coordination procedures, in particular the cost due to iterations, is of high managerial interest and the method provides a comprehensive tool for strategic IT decision making.Originality/valueReviewed literature is mostly focused on the benefits of SCM software implementations. However, ERP system based supply chain coordination is still widespread industrial practice but associated coordination cost has not been addressed by researchers.

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Coordination mechanism of IT service supply chain: an economic perspective

Cited by 14 publications

References 17 publications

Sharing Economy Platforms’ Pricing Strategies and Decision Preferences: The Example of DiDi

Sharing Economy Platforms’ Pricing Strategies and Decision Preferences: The Example of DiDi

Exploratory Research on the Relationship Between Digital Service Supply Chain Capability and Supply Chain Performance

Evaluating alternative industrial network organizations and information systems

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