Analyzing the interaction of critical factors of supplier development using Interpretive Structural Modeling—an empirical study

Chidambaranathan, S.; Muralidharan, C.; Deshmukh, S.G.

doi:10.1007/s00170-008-1788-7

Cited by 64 publications

(31 citation statements)

References 18 publications

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“…The authors provided a decision support system to allocate an investment of a company to its suppliers, such that a target return is achieved at a minimum risk. Recent reviews of works on supplier development are those of Chidambaranathan et al (2009) andWagner (2011), who showed that the majority of works on supplier development presented empirical studies based on surveys. Another stream of research that is relevant for this paper studies investments into process improvements and/or variable production rates.…”

Section: Literature Reviewmentioning

confidence: 99%

A joint economic lot size model with financial collaboration and uncertain investment opportunity

Marchi

Ries

Zanoni

et al. 2016

International Journal of Production Economics

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Establishing long-term relationships among the members of a supply chain has become necessary to enhance the supply chain's competitiveness in a globalized environment. Besides coordinating operational decisions, such as how much and when to produce or to order, the members of a supply chain may also share financial resources or act jointly on the capital market. This is important especially when companies have unequal access to capital, for example because they are located in countries with different economic conditions and banking policies and/or ratings. The joint financing of investments across the supply chain may thus ensure the stability of production and of the flow of products to the customers. In addition, it strengthens the established relationships among the supply chain members. This study takes up these issues and presents an integrated inventory model that considers investments jointly financed by the members of a supply chain. In particular, it considers a two-stage supply chain with a single vendor and a single buyer and assumes that the vendor has the option to invest in increasing its production rate. The buyer, however, is assumed to have better access to capital, and therefore has the option to give a credit to the vendor to invest in its productivity, which is beneficial for both parties. To consider uncertainties of the production improvement investments, a success probability for the investment is considered and modeled using a beta distribution.

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Section: Literature Reviewmentioning

confidence: 99%

A joint economic lot size model with financial collaboration and uncertain investment opportunity

Marchi

Ries

Zanoni

et al. 2016

International Journal of Production Economics

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show abstract

“…Level-1 perception gaps often imply the need for organizational level communication, openness in sharing information across supply chain (between organisations) [53], closer alliances in setting strategic goals [54], supplier development [55], and defining market positioning. Furthermore, Level-1 gaps may also suggest the need for coordination mechanisms, such as the appropriate design of the contracts between the buyer and supplier [56,57] or coordinated inventory planning [58], which can significantly increase supply chain performance. The Level-2 gaps are the perception variations, also with a collective view of organisation, but between the different suppliers (or buyers) within the same tier.…”

Section: Three-level Gaps Modelmentioning

confidence: 99%

Modelling the supply chain perception gaps

Lü

Ertek

Betts

2013

Int J Adv Manuf Technol

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This study applies the research of perception gap analysis to supply chain integration and develops a generic model, the 3-Level Gaps Model, with the goal of contributing to harmonization and integration in the supply chain. The model suggests that significant perception gaps may exist among supply chain members with regards to the importance of different performance criteria. The concept of the model is conceived through an empirical and inductive approach, com-bining the research discipline of supply chain relationship and perception gap analysis. First hand data has been collected through a survey across a key buyer in the motor insurance industry and its eight suppliers. Rigorous statistical analysis testified the research hypotheses, which in turn verified the validity and relevance of the developed 3-Level Gaps Model. The research reveals the significant existence of supply chain perception gaps at all three levels as defined, which could be the root causes to underperformed supply chain.

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“…Wang et al [23] To analyze the interactions among the barriers to energy-saving projects in China. Chidambaranathan et al [24] To develop the structural relationship among supplier development factors and to define the levels of different factors based on their dependence power and mutual relationships. Kannan et al [25] To construct a multi-criteria group decisionmaking (MCGDM) model through ISM and fuzzy technique for order preference by similarity to ideal solution (TOPSIS) to guide the selection process of best third-party reverse logistics providers.…”

Section: Authors Theories or Applicationsmentioning

confidence: 99%

An Integrated Multi-Criteria Decision Making Model for Evaluating Wind Farm Performance

et al. 2011

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Abstract:The demands for alternative energy resources have been increasing exponentially in the 21st century due to continuous industrial development, depletion of fossil fuels and emerging environmental consciousness. Renewable energy sources, including wind energy, hydropower energy, geothermal energy, solar energy, biomass energy and ocean power, have received increasing attention as alternative means of meeting global energy demands. After Japan's Fukushima nuclear plant disaster in March 2011, more and more countries are having doubt about the safety of nuclear plants. As a result, safe and renewable energy sources are attracting even more attention these days. Wind energy production, with its relatively safer and positive environmental characteristics, has evolved in the past few decades from a marginal activity into a multi-billion dollar industry. In this research, a comprehensive evaluation model is constructed to select a suitable location for developing a wind farm. The model incorporates interpretive structural modeling (ISM), benefits, opportunities, costs and risks (BOCR) and fuzzy analytic network process (FANP). Experts in the field are invited to contribute their expertise in evaluating the importance of the factors and various aspects of the wind farm evaluation OPEN ACCESSEnergies 2011, 4 2003 problem, and the most suitable wind farm can finally be generated from the model. A case study is carried out in Taiwan in evaluating the expected performance of several potential wind farms, and a recommendation is provided for selecting the most appropriate wind farm for construction.

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Analyzing the interaction of critical factors of supplier development using Interpretive Structural Modeling—an empirical study

Cited by 64 publications

References 18 publications

A joint economic lot size model with financial collaboration and uncertain investment opportunity

A joint economic lot size model with financial collaboration and uncertain investment opportunity

Modelling the supply chain perception gaps

An Integrated Multi-Criteria Decision Making Model for Evaluating Wind Farm Performance

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