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This paper aims to examine how collaborative supplier development (SD) activities, supplier capabilities and buyer–supplier relationship interrelate in technology-based, luxury product business contexts characterized by small volumes, difficult targets and resource constraints relative to those targets.

Using inductive case research method, the authors investigate multiple embedded cases involving six dyadic buyer–supplier relationships of two luxury product manufacturers in the motorcycle and automotive industries. Each dyad represents an important sub-system for which the buying firm committed significant SD efforts to help the supplier successfully achieve difficult targets.

The analysis reveals how paradoxical tensions might emerge as the firms engage in successful SD activities, which could lead to decreasing relationship commitment ultimately resulting in the termination of the relationship. The authors utilize the “value co-creation and value capture” paradox framework to understand the SD and relationship dynamic and characterize it as developing-leveraging paradox to explain its dualities, i.e. commitment-based SD efforts (increasing value co-creation), and unilateral leveraging of the newly acquired capabilities (increasing value capture) by both the buyer and the supplier. Overemphasis on value capture by one of the exchange partners spurs a detrimental vicious cycle leading to the decline of the relationship.

The study explains the paradoxical dynamics that may emerge in SD activities of innovative, technologically complex, luxury product firms. The findings contribute to the SD literature by highlighting how learnings from SD activities could contribute to the dark sides of buyer–supplier relationship. The technologically complex, luxury product contextual characteristics of the study may limit the generalizability of the study findings.

The study provides novel insights into the emergence and management of paradoxes in buyer–supplier relationships, in terms of virtuous and vicious dynamics of developing-leveraging.

The purpose of this paper is to examine the buyer–supplier exchange dynamic in terms of the influence of product and market contingencies on the interfirm connectivity, governance and exchange performance of interconnected dyads in multitier supply chains (MSCs).

Using an inductive approach, the authors analyzed the supply network of a high-end motorcycle manufacturer (OEM). Four sets of “interconnected dyads” constituting four embedded units of analysis were considered, each involving the OEM, its tier 1 and corresponding tier 2 suppliers. These interconnected dyads representing four strategic components and their sub-components offer contrasts in terms of product and market contingencies.

This analysis reveals that product and market contingencies influence patterns of dependence among firms. These in turn impact interfirm connectivity (i.e. structural characteristic), and the degree of contract formalization, collaboration and concentration of decision-making power (i.e. governance characteristics) in the interconnected dyads. The authors also found that structural and governance aspects can have mutual influence, leading to satisfactory or unsatisfactory outcomes. Propositions synthesizing the relationships among the constructs are developed.

The constructs and their underlying relationships need to be further refined if we are to devise hypotheses and validate them at a large-scale empirical level.

This is one of the first studies to explore the influence of business contingencies on the complex buyer–supplier exchange dynamic in MSCs having a “beyond the dyad” perspective. The authors address why and how various types of interconnectivity are developed, and how the interplay among interfirm dependence, connectivity and governance influences the suppliers’ performance in the MSCs.

Supply chain performance (SCP) extent can be attributed as a function of multiple criteria/attributes. Most of the criterions/attributes being intangible in nature; SCP appraisement relies on the subjective judgment of the decision makers. Moreover, quantitative appraisement of SCP appears to be very difficult due to involvement of ill-defined (vague) performance measures as well as metrics. The purpose of this paper is to develop an efficient decision support system (DSS) to facilitate SCP appraisement, benchmarking and related decision making.

This study explores the concept of fuzzy logic in order to tackle incomplete and inconsistent subjective judgment of the decision makers’ whilst evaluating supply chain’s overall performance. Grey relational analysis has been adopted in the later stage to derive appropriate ranking of alternative companies/enterprises (in the same industry) in view of ongoing SCP extent.

In this work, a performance appraisement index system has been postulated to gather evaluation information (weights and ratings) in relation to SCP measures and metrics. Combining the concepts of fuzzy set theory, entropy, ideal and grey relation analysis, a fuzzy grey relation method for SCP benchmarking problem has been presented. First, triangular fuzzy numbers and linguistic evaluation information characterized by triangular fuzzy numbers have been used to evaluate the importance weights of all criteria and the superiority of all alternatives vs various criteria above the alternative level. Then, the concept of entropy has been utilized to solve the adjusted integration weight of all objective criteria above the alternative level. Moreover, using the concept of the grey ration grades, various alternatives have been ranked accordingly.

Finally, an empirical example of selecting most appropriate company has been used to demonstrate the ease of applicability of the aforesaid approach. The study results showed that this method appears to be an effective means for tackling multi-criteria decision-making problems in uncertain environments. Empirical data have been analysed and results obtained thereof, have been reported to exhibit application potential of the said fuzzy grey relation based DSS in appropriate situation.

The purpose of this paper is to investigate two-dimensional viscous incompressible magnetohydrodynamic boundary layer flow and heat transfer of an electrically conducting fluid over a continuous moving flat surface considering the viscous dissipation and Joule heating.

Suitable similarity variables are introduced to reduce the governing nonlinear boundary layer partial differential equations to ordinary differential equations. A numerical solution of the resulting two-point boundary value problem is carried out by using the finite element method with the help of Gauss elimination technique.

A comparison of obtained results is made with the previous work under the limiting cases. Behavior of flow and thermal fields against various governing parameters like mass transfer parameter, moving flat surface parameter, magnetic parameter, Prandtl number and Eckert number are analyzed and demonstrated graphically. Moreover, shear stress and heat flux at the moving surface for various values of the physical parameters are presented numerically in tabular form and discussed in detail.

The work is relatively original, as very little work has been reported on magnetohydrodynamic flow and heat transfer over a continuous moving flat surface. Viscous dissipation and Joule heating are neglected in most of the previous studies. The numerical method applied to solve governing equations is finite element method which is new and efficient.

The purpose of this paper is to outline and prioritizes risk sources in medical device development (MDD) process using an integrated “structural equation modeling” (SEM) and fuzzy “technique for order performance by similarity to ideal solution (TOPSIS)” framework.

Risk sources which deter MDD process are explored through literature review. Initial structural model is proposed, factor loadings are determined by exploratory factor analysis and model fit is established by confirmatory factor analysis. Further, the sources are ranked using FTOPSIS, and sensitivity analysis is carried to check robustness of results.

The sources of risks have catastrophic effect on MDD process. The initial SEM model developed based on survey of experts is found reliable and valid which breaks up the risk sources into three categories – internal sources of risks, user-related sources of risks and third-party-related sources of risks. The risk sources are ranked and prioritized based on perspective of experts from the categories using FTOPSIS; unmet user needs/requirements is found as the most important source of risk. Results of sensitivity analysis confirm that the factors are relatively less sensitive to criteria weights confirming reliability of initial solution.

The proposed methodology combines qualitative and quantative approaches, making it little complex and lengthy, but results in dual confirmation.

The outcomes of this research will be of prime use for MDD industries to mitigate risk sources. It will help to increase the success rate of MDD.

Integrated SEM-FTOPSIS provides a unique and effective structural modeling-based decision support tool. The framework can be effectively utilized in other domains, and failure events of medical devices can be potentially controlled by applying risk mitigation measures.

International projects very commonly experience failure due to various factors at the global level. Especially, large projects at the international level virtually have no chance of meeting scope, time, cost and quality. This fact has been underlined by most of the international surveys and published literature. Effective risk management plays a vital role in preventing projects from failure by implementing appropriate risk response strategies. The success of risk management will be based on the understanding of various risk categories which specifically affect international projects, analysis of their interdependence, prioritize them according to their importance and develop strategies for risk management based on the prioritization. The paper aims to discuss these issues.

This paper represents typical eight risk categories frequently observed in the international projects through literature survey and feedback from project professionals. Interpretive structural modeling (ISM) and Matrice d’Impacts croises-multiplication applique´ an classment (MICMAC) analysis have been used to analyze the interactions among the risk categories and prioritize them. The strategy management tool threats, opportunities, weaknesses and strengths (TOWS) matrix has been used to develop the strategies for effective project risk management.

The analysis represents political risks, contractual and legal risks, cultural risks, and financial and economic risks as the highest priority risk categories, the mitigation of which should be paid the highest attention. The strengths-threats strategy has been applied to develop the strategies by identifying the various internal strengths of project organization to overcome the various threats caused by the eight risk categories observed in international projects.

This paper tries to represent the prioritization of international project risk categories which are generic in nature. For any specific international project, the risk categories as well as their prioritization may be slightly varying. The tool used for prioritization; Interpretive structural modeling (ISM) is more suitable for few numbers of variables as it becomes complex as the number of variables increases. The strengths and threats considered for developing strategies using TOWS matrix are based on the feedback from project professionals and may vary according to the nature of project.

This paper uses ISM and MICMAC for risk prioritization in international projects and TOWS matrix for developing risk management strategies. This may trigger new opportunities for in-depth research in the risk management strategy development for international projects.

Due to climate change and a considerable increase in man-made disasters, disaster risk management has gained a lot of importance. This article aims to summarize the proceedings of two days of discussion on natural and human-induced disasters organized by National Institute of Disaster Management at Vigyan Bhavan, New Delhi. The objective is to evolve a holistic national strategy for inclusion of disaster risk reduction (DRR) policies and programs into the mainstream of developmental activities. The libraries worldwide are witnessing a series of disasters, and DRR is one of the much-discussed topics within the library community. The literature on disaster risk management in libraries is scanty, and with less research being done, needs urgent attention. The library conferences in India and abroad hardly address the theme “DRR”; therefore, this report will be of interest to librarians and policy makers for libraries.

This report includes selected presentations and discussion during thematic and plenary sessions and provides a review of some of the events of the first session of the National Platform for Disaster Risk Reduction (NPDRR). The author's observation/participation and discussion on vital areas, namely disaster resilience, capacity building, risk insurance, global warming and climate change, created insight in preparation of this report.

A multi-stakeholder NPDRR has been constituted by the Government of India, with Home Minister as Chairman, in Resolution No. 47-31/2012-DM-III on 26 February 2013. The event was attended by various stakeholders such as policy makers, administrators, professional disaster managers, UN organizations, multilateral organizations, scientists, technocrats, academicians, corporate and private sectors, community leaders, representatives of Panchayati Raj Institutions (grass roots-level institutions in India preferably called a “village panchayat”), and NGOs. India is amongst 80 countries which have a national platform on disaster risk management like the NPDRR. The theme generated a lot of discussion on risk financing mechanisms, long-term recovery and rehabilitation, and holistic strategy for multi-hazard DRR.

This is an important topic in the area of disaster risk management which includes disaster resilience, capacity development, and policy planning. This discussion forum facilitated the enhancement of knowledge and the integration of DRR into the mainstream of development.

Information sharing helps improve the efficiency of the supply chain. However, there are some problems in the multi-stage structure supply chain, such as untimely information feedback and distortion. Despite recent progress in ensuring improved collaboration in the past decade or so, the inefficiency status continues to persist. It is also difficult to add value to the supply chain. The information sharing framework and decentralized model designed in this paper are to deal with existing problems.

This paper is based on the theoretical research of supply chain information asymmetry and synergetics. We attempt to introduce blockchain technology into supply chain operation management, reconstruct information sharing architecture and provide a new decentralized mode to promote the collaborative operation of all nodes. The information sharing and decentralization operational model are built, which has changed the hierarchical relationship between upstream and downstream enterprises, regarding customers as the center of the whole system and effectively reducing the bullwhip effect. Finally, we selected the home supply chain as an example design and performed system dynamics simulation on the blockchain-based operation process.

The model of setting up the scene application mode based on blockchain is helpful to realize the goal of supply chain management to reduce cost, improve quality and enhance the overall efficiency of the system.

Based on the blockchain technology, this paper constructed a new supply chain operation mode and used the synergetic theory and the concept of the product–service system to explain the process of value increment in detail.

The purpose of this paper is to develop a green supplier development (GSD) process model and validate the model with a case study in Indian automobile industry.

A literature survey of peer-reviewed journal articles, survey reports and paradigmatic books with managerial impact is done for the research. The process of GSD is modeled using stage-gate approach and KPIV and KPOV of the process are determined. The process model is implemented in an Indian automobile components manufacturing industry for validation.

The industry implemented the model with ten suppliers and was able to successfully convert seven of them into Green suppliers. Remaining three suppliers were asked to repeat the process again or terminate the contracts. Model implementation took around three years starting from planning of resources and finances to actual development of suppliers.

The model implementation was done with a small automobile industry and hence the validation and implications may be generalized by taking the case study further in different industries. It would be beneficial to test the model with case studies of large-scale industries.

The process model for implementing GSD activities will help managers in taking complex investment decisions. The stages and process inputs and outputs are clearly defined which helps the managers to successfully develop the suppliers.

This paper puts forward the process model that should be implemented for the successful development of green suppliers. It might represent new opportunities for rigorous and relevant research in the area of green supply chain.

With respect to the multiple-attribute decision-making problem with subjective preference for a certain attribute whose weight-value range have been given over other attributes whose weight values are unknown, a method based on the mean value of the grey number is proposed to analyse the decision-making problem. This method is used to choose a supply-chain partner under the condition that the decision makers have a preference for a certain attribute of various alternatives. The paper aims to discuss these issues.

First, the middle value of the preferred attribute’s weight-value range is supposed to be its weight value according to the content of the mean value of the grey number. Second, to reflect the decision maker’s subjective preference information, an improved optimisation model that requests the minimum deviation between the actual and expected numerical value of each attribute is constructed to assess the attributes’ weights. Third, the correlated degree and the correlation matrix, which are determined by the weight values of all attributes, are used to rank all the alternatives.

This paper provides a method for making a decision when decision makers have a preference for a certain attribute from an array of various alternatives, and the range of the certain attribute’s weight value is given but the weight value of the other attributes is unknown. When applied to supply-chain partner selection, this method proves feasible and effective.

This method is feasible and effective when applied to supply-chain partner selection, and can be applied to other kinds of decision-making problems. This means it has significant theoretical importance and extensive practical value.

Based on the mean value of the grey number, an optimisation model is built to determine the importance degree of each attribute, then the correlated degree of each alternative is combined to rank all the alternatives. This method can suit the decision makers’ subjective preference for a certain attribute well.