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Many developing countries, including India, are committed to curbing black money from the economy. Therefore, these countries are focusing on a transparent online transaction facility. M-wallets are one online option facilitated by various companies using a mobile application. The purpose of this paper is to investigate the impact of perceived usefulness, perceived security, perceived ease of use, trust, grievance redressal and satisfaction on young users’ intention to continually use M-wallet in India.

A research framework based on the expectation–confirmation theory has been formulated and tested empirically using data from M-wallets young users in India using structural equation modeling.

The analysis reveals that perceived usefulness and perceived ease of use significantly affect user satisfaction and intention to continually use M-wallets. The effect of perceived security on user satisfaction is significant, and grievance redressal mediates the effect of perceived security on intention to continually use M-wallets.

The outcome of the research will help M-wallet service providers and policy makers in planning the service and increasing customer’ continuance intention.

The uniqueness of this research is that it adds two important constructs for mobile payment systems (grievance redressal and perceived security) that were missing in the earlier model proposed by Zhou (2013). The addition of the two constructs helped in formulating a better model.

Approximately, 800m tons of e-waste is generated per year in India. Reverse supply chain (RSC) is the probable strategy to cope up with the issue. Setting up a RSC process is not popular in the Indian sector. There are several factors that basically control the profitability of such kind of business. Hence, the purpose of this paper is to develop a causal model among the identified issues and sub-issues for setting up a RSC in an Indian semiconductor manufacturing industry and then evaluate the critical issues based on the causal relations.

Decision-making trial and evaluation laboratory (DEMATEL) method along fuzzy set theory is used to develop the causal framework among the identified strategical and tactical issues. According to the causal relations from DEMATEL, analytical network process is then used to identify the weights of the sub-issues.

The cause–effect interactions among the main issues show that legislations and regulations, market-related issues and organizational issue are the most significant strategic issues. Uncertainty in the acquisition time is the most significant tactical issue because it has a crucial impact on the quality and quantity of the used products. Based on the obtained causal relations of the main issues, it is identified that the reduction of waste, creation of new opportunity, market competition, cost reduction, change in technology and location, capacity and number of recovery facility are the major sub-issues in RSC implementation.

This study is conducted on the basis of the experts’ opinion from a semiconductor manufacturing industry, situated in the southern part of India. Therefore, this proves its practical implications.

The paper provides the detail illustration of the issues in the RSC process, and the prioritization of the issues based on the cause–effect relationships also provides some meaningful managerial insights.

The purpose of this paper is to capture the dynamic variations in sales of a product based upon the dynamic estimation of the time series data and propose a model that imitates the price discounting and promotion strategy for a product category in a retail organization.

Time series data relating to sales has been used to model the sales estimates using moving average and proportional and derivative control; thereafter a sales forecast is generated to estimate the sales of a particular product category. This provides valuable inputs for taking lot sizing decisions regarding procurement of the products and selection of suppliers. A hybrid model has been proposed and explained with a hypothetical case, which considerably impacts the sales promotion and intelligent pricing decisions.

A conceptual framework is developed for modeling the dynamic price discounting strategy in retail using fuzzy logic. The model imitates sales promotion and price discounting strategy. This has helped minimize the inventory cost thereby keeping the profitability of the retail organization intact.

There is no appropriate empirical data to verify the models. In light of the research approach (modeling based upon historical time series data of a particular product category) that was undertaken, there is a possibility that the research results may be valid for the product category that was selected. Therefore, the researchers are advised to test the proposed propositions further for other product categories.

The study provides valuable insight on how to use the real-time sales data for designing a dynamic automated model for product sales promotion and price discounting strategy using fuzzy logic for a retail organization.

The purpose of this article is to provide an overview and evaluation of performance measurement systems and also present a framework for the selection of an appropriate performance measurement system for healthcare processes.

The paper provides a brief review of the existing performance measurement frameworks. On the basis of review, performance measurement system criteria are identified and accordingly a framework has been proposed for measuring performance in healthcare processes.

The measurement of performance of a healthcare organization is still an unresolved issue. A performance measurement system should be sensitive to changes in the external and internal environment of an organization. The proposed framework measures performance from a multi and interrelated perspective, namely efficiency, effectiveness and flexibility.

The study will help the healthcare organization to know how they are performing; it will also help in benchmarking the organization so that customers know the value of the money they pay for the service.

The framework presented provides a performance measurement system for healthcare processes that is sensitive to change in the external and internal environment of an organization.

A variety of tools are available to measure supply chain efficiency, but there are a few methods available for assessing efficiency in dynamic environments. The purpose of this paper is to illustrate the use of data envelopment analysis (DEA) with the help vector auto regression in measuring internal supply chain performance in dynamic environment.

Two DEA models were developed – the static DEA that is traditional DEA methodology and the dynamic DEA. The models are further enhanced with scenario analysis to derive more meaningful business insights for managers in making benchmarking and resource planning decisions.

The results demonstrate that lagged effects can lead to changes in efficiency scores, rankings, and efficiency classification. So, using static DEA models in dynamic environment can be potentially misleading. Using impulse response analysis it has been seen that shocks given to marketing strategy in MR affects more at each of the decision-making unit’s (DMU’s) compared to other variables, further the authors could also investigate the dependent variables (output) shocks to input variables.

Methodology can be applied to a wide range of evaluation problems in place of conventional DEA models. Results show that lagged effects can lead to substantial discrepancies in evaluation results. Biased evaluation results would easily lead to erroneous decision and policy making for the firm. Therefore the authors should always take a broader perspective in evaluating longitudinal performance by incorporating the effects into evaluation and decision-making processes. Future work of this study could look into the possibility of modeling in a stochastic supply chain environment. In addition, it will also be interesting to look into evaluating the stochastic DEA model in multiple time periods in order to examine whether there is any technological influence on the supply chain efficiency.

The contribution of this study provides useful insights into the use of DDEA as a modeling tool to aid managerial decision making in assessing supply chain efficiency in dynamic environment.

The objective of this work is to develop a model that can be used for simulation of different parameters including price, subjected to different control strategies.

The entire supply chain can be modelled by combining the transfer function into a closed loop system. The transfer function of each entity in the supply chain can be obtained by using the control theory tools. The model can be approximated as a linear discrete system with various operating constants, like lead time, price, order policy and supply.

The continuous replenishment ordering policy for a distribution node in a supply chain was analyzed using the z-transform. Characteristic equations of the closed loop transfer function are obtained. The bullwhip (BW) effect is analyzed. Study proves that the BW effect is in evitable if the standard heuristic ordering policy is employed with demand forecasting; also the paper analysed price supply trade-off for dynamic demand and supply. Simulation results show that BW is less in PI and simple p-only with cascade control. Robust control and PD, PID control results are not shown in this literature, and it is subject to further research.

Research is original, it can be applicable in today's dynamic world, due to globalization, it is necessary to have a automated machine that can handle most of supply chain decision.