Structural model for analysis of key performance indicators for sustainable manufacturer–supplier collaboration: A grey-decision-making trial and evaluation laboratory-based approach

With growing competition in the market and dire need for sustainability, it has become imperative for companies to build long-term relationship with their supply chain partners through sustainable collaboration. Among these, the supplier–manufacturer relationship is crucial for improved organizational, business and sustainable performance. Sustainable collaboration with suppliers involves crucial decision-making processes such as continuous supplier monitoring and supplier development. Hence, a critical challenge that a company faces is to identify the key performance indicators (KPIs) for assessing the performance of a supplier for sustainable collaboration. In this regard, this study focuses on identification of KPIs for an Indian home appliance company through exhaustive discussions involving multiple decision-makers. Further, a grey-based decision-making trial and evaluation laboratory (DEMATEL) model is proposed in the study for analysing the importance levels among the fifteen KPIs based on multiple stakeholder perspectives. The results of the grey structural model indicate seven KPIs as influencing KPIs and eight KPIs as influenced KPIs. The KPI ‘Information disclosure’ has been identified as the most influential KPI for the evaluation of suppliers for sustainable collaboration. The implications drawn from the result analysis model can provide meaningful insights to managers for identifying strategies towards strengthening the supplier–manufacturer relationship and achieving organizational and market competence.     

Reconciling Observed Tariffs and the Median Voter Model

Median voter theory applied to trade policy predicts positive tariffs in capital‐abundant countries and negative tariffs in labor‐abundant countries. Negative tariffs are rare, and this paper reconciles the median voter theory with observed protectionism across countries. By considering large countries, I show the optimal tariff is a sum of the median voter component and a positive term of trade component. Positive terms of trade effects raise tariffs in all countries, and can overcome the negative median voter component in labor‐abundant countries. Testing the tariff prediction with cross‐section and panel data from the 1990s, I show the median voter component is negative in labor‐abundant countries and positive in capital‐abundant countries. As expected, terms of trade effects raise tariffs across all countries and are stronger among nonmembers of the WTO.     

Modeling the key factors influencing the adoption of mobile financial services: an interpretive structural modeling approach

Mobile financial services are widely appreciated worldwide, but a considerable fragment of the population is resisting the technology. Therefore, the purpose of this paper is to identify and analyze the contextual relationships among a set of measures that influence the adoption of mobile financial services (MFSs). The paper employed the interpretive structural modeling technique to formulate a multilevel structural model with experts' knowledge and experience. Using MICMAC analysis, the factors were classified into four clusters: autonomous, linkage, dependent, and driving based on their dependence and driving power. The outcome shows that facilitating conditions is the most crucial factor in influencing the MFS adoption and demands special attention by authorities for better implementation of the technology. The findings will help the bank managers and telecom companies to direct their resources in significant areas.