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One of the major challenges for developing countries is the lack of mechanisms for the evaluation of critical success factors (CSFs) of quality initiatives, which hampers the journey toward sustainability. Lean Six Sigma (LSS) has been one of the most widely used initiatives supporting quality improvement with wastes reduction and facilitating sustainability. To expedite LSS and its spread, it is important to evaluate key CSFs. Accordingly, the purpose of this paper is to provide an approach for the evaluation of LSS-CSFs for Indian small and medium enterprises (SMEs).

The paper uses a graph theoretic approach and demonstrates the evaluation of LSS-CSFs by proposing an index. The development of index is illustrated using a set of seven prioritized CSFs based on the literature review paper (Lande et al., 2016).

This study guides about the translation of CSFs in the form of an index (number) and will benefit both researchers and practitioners, who wish to study the role of key CSFs for implementation and audit requirements for sustainability.

Authors remain confined only to Indian SMEs.

LSS possesses the potential to enhance the performance of manufacturing SMEs, but its evaluation is not easy. This attempt for offering a useful evaluation scheme involving CSFs, in the areas of LSS in developing country contexts, is the first. The approach also facilitates both quality audits and benchmarking between different sets of CSFs. The approach is generalizable and can be extended in other areas.

A geographically proximate group of rice mills, supporting companies, suppliers, and associated institutions in a particular field is emerging as a concept to make rice mills more competitive. The factors, which emerged due to cluster formation, appear to have the potential to contribute to the performance of rice mills. The purpose of this paper is to investigate the effect of a rice mill cluster initiative. The primary objective is to identify the critical factors of a successful rice mill cluster initiative. To meet this objective, a questionnaire is developed for the assessment of effects of cluster elements.

The methodology used for this paper is an exploratory cross‐sectional and literature review of published materials.

There is strong evidence to suggest that a cluster policy brings additional positive effect to existing small enterprises such as rice mills located in a cluster.

This study offers initial empirical evidence and a number of important insights to assist managers and policy makers in enhancing performance of rice mills located in a cluster. The findings from this research will assist strategy makers in making more informed decisions regarding the adoption of a cluster approach and entering into cluster‐based relations, as well as assisting policy makers in designing more efficient cluster policies. The academic value will be added in the context of expanding knowledge in relation to the impact of clusters on economic development in developing countries and as such contribute in filling gaps within the existing literature.

Profit analysis of a two non‐identical unit cold standby system model with mutual changeover of the units is carried out in this paper. With mutual changeover of the unit, the operating unit, after functioning for some random amount of time, becomes standby to take rest, and the standby unit becomes operative. The failure and repair times of each unit are jointly distributed as bivariate exponential (BVE) with different parameters. Various measures of system effectiveness useful to system engineers and designers are obtained by using the regenerative point technique. Behaviour of the mean time to system failure (MTSF) and availability have also been studied graphically.

This intervention study outlines the continuing journey of a university towards its sustainability potentiality. We introduce the importance of sustainable development and link it to our intervention study of potentiality for sustainability from a Heideggerian phenomenological perspective. Through a case study of sustainability at New Mexico State University, we provide an insight into the development of a new dimension of university sustainability interface. This interface exists in terms of a dialogic of sustainability, as it relates to the balancing of competing needs, such as efficiency, heart, and brand identity. An important aspect of this interface is intervention, highlighting new possibilities for the top administrators regarding the university's goals and environmentalities. A qualitative and interpretive approach using ontological storytelling inquiry is employed. Data for the study were collected through in-depth interviews with university members from all hierarchical levels. This article raises interesting ontological issues for sustainability researchers, and has implications for strategy as practice.

Firms have been adopting lean manufacturing to improve their business performances. However, they are facing failures or less success in implementation, mainly due to lack of understanding in relating the lean practices (LPs) from the required performance measures perspective. In view of the lack of research and the importance of understanding them, the purpose of this paper is to prioritize LPs.

As LPs are scattered in the literature and a variety of performance measures are used, an extensive literature review is first carried out to identify the LPs and performance measures. The blend of interpretive structural modeling and interpretive ranking process interpretive tools is adopted in establishing the contextual relationship among LPs and then ranking them based on the performance measures. A three-dimensional priority matrix is proposed for better explanation of the results.

The proposed framework can help firms better understand LPs and their levels of importance in lean implementation.

The involvement of lean experts may produce some bias in evaluating the LPs.

The proposed framework can help practitioners to develop an industry-specific road-map for the result-oriented LP implementation. Based on the area of performance to be improved, practitioners can prioritize LPs for implementation.

This is the first study that provides a comprehensive review of LPs available in the literature and prioritizes them in accordance with performance with interpretive tools.

In a volatile agricultural postharvest market, producers require more personalized information about market dynamics for informed decisions on the marketed surplus. However, this adaptive strategy fails to benefit them if the selection of a computational price predictive model to disseminate information on the market outlook is not efficient, and the associated risk of perishability, and storage cost factor are not assumed against the seemingly favourable market behaviour. Consequently, the decision of whether to store or sell at the time of crop harvest is a perennial dilemma to solve. With the intent of addressing this challenge for agricultural producers, the study is focused on designing an agricultural decision support system (ADSS) to suggest a favourable marketing strategy to crop producers.

The present study is guided by an eclectic theoretical perspective from supply chain literature that included agency theory, transaction cost theory, organizational information processing theory and opportunity cost theory in revenue risk management. The paper models a structured iterative algorithmic framework that leverages the forecasting capacity of different time series and machine learning models, considering the effect of influencing factors on agricultural price movement for better forecasting predictability against market variability or dynamics. It also attempts to formulate an integrated risk management framework for effective sales planning decisions that factors in the associated costs of storage, rental and physical loss until the surplus is held for expected returns.

Empirical demonstration of the model was simulated on the dynamic markets of tomatoes, onions and potatoes in a north Indian region. The study results endorse that farmer-centric post-harvest information intelligence assists crop producers in the strategic sales planning of their produce, and also vigorously promotes that the effectiveness of decision making is contingent upon the selection of the best predictive model for every future market event.

As a policy implication, the proposed ADSS addresses the pressing need for a robust marketing support system for the socio-economic welfare of farming communities grappling with distress sales, and low remunerative returns.

Based on the extant literature studied, there is no such study that pays personalized attention to agricultural producers, enabling them to make a profitable sales decision against the volatile post-harvest market scenario. The present research is an attempt to fill that gap with the scope of addressing crop producer's ubiquitous dilemma of whether to sell or store at the time of harvesting. Besides, an eclectic and iterative style of predictive modelling has also a limited implication in the agricultural supply chain based on the literature; however, it is found to be a more efficient practice to function in a dynamic market outlook.

Presents the analysis of a two‐unit cold standby system in which the standby unit takes a random amount of time for operation whenever the operative unit fails. Each unit is first repaired by the assistant repairman and is then taken up for post‐repair if necessary. The failure and repair times of each unit are assumed to be correlated and their joint density is taken as bivariate exponential. Uses regenerative point technique to obtain various reliability characteristics of interest. Studies the behaviour of steady‐state availability through graphs. Verifies earlier results.

Investigates a stochastic model of a two identical unit cold standby system. Assumes that, if repair of the failed unit is not completed within a specified time, then an order is placed to replace the failed unit by the new one. The specified time is also known as the maximum repair time limit which may change from user to user of the system, so that it is assumed as a random variable. Joint distribution of failure and repair times is bivariate exponential whereas the distributions of lead time (difference between order and delivery time for a new unit) and replacement time of the new unit are negative exponential. Obtains various reliability characteristics of the system under study by using regenerative point technique. Also studied characteristics through graphs.

Deals with the stochastic analysis of a two identical unit cold standby system model with repair and replacement policies. Taking the bivariate exponential distribution of failure and repair times and using the regenerative point technique, various measures of system effectiveness are obtained.

Due to technology advancement or transparency in system, there is a constant inflow and outflow of technology in the business for transparency and efficiency. To seize a competitive advantage, companies have emerged new technological solutions to respond to the change in the organization environment. There is a surge in the requirement of learning opportunities and effective training programs in the organization. The current study has been an effort to understand the potential of blockchain technology that can create better training evaluation.

The electronic-Delphi (e-Delphi) method has been conducted by recording the final consensus and to find a balance for implementation of blockchain technology and measuring training effectiveness. The current research is one of its new types where blockchain-enabled training effectiveness measurement (BETEM) model has been formulated using a qualitative approach.

The study has considered human resource (HR) professionals as the experts and based on their responses, the formulation of theoretical network model has been structured using e-Delphi–BETEM (e-DLH–BETEM) approach. By critically examining the experts’ responses and comments, the study formulated the four major themes and 11 subthemes for the smooth functioning of the BETEM for an organization.

The research aims to aid innovations in BETEMs model for training evaluation. The model will contribute incrementally toward the complete transformation of the training development programs of employees. The goal of BETEMs is to ensure that organizations, specifically HR personals can prepare themselves to have competitive advantage by using blockchain technology.

The application of blockchain technology in measuring the training effectiveness is an addition to existing literature as majority of existing studies have studied the use of technology for measuring training effectiveness.