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This paper aims to analyze the agile manufacturing practices in small and medium enterprises (SMEs) within the auto-ancillary sector spread across eastern India. Using statistical method, a number of crucial insights have been captured and discussed in detail.

A structural equation model (SEM) encapsulating pertinent agile manufacturing attributes and enablers as the focal construct is conceptualized and validated in this research. The SEM model is evolved in a manner that agile attributes and agile enablers are modeled as latent dependent and manifest variable, respectively.

A number of key hypothesis entailing interactions of key agility enablers, i.e. manufacturing responsiveness agility, manufacturing strategy agility, workforce agility, technology agility, manufacturing management agility, etc. are conceptualized and validated.

The authors specifically focus on evolving agile manufacturing framework (characterized by agility enablers and attributes) that lies at the intersection of SMEs, automotive sector and an emerging economy.

The purpose of this paper was to examine the perceived outcomes of e-learning by identifying key attributes affecting user (learner) satisfaction in higher education institutes.

A conceptual model considering user satisfaction as a key construct was developed through critical literature review and expert opinion. The model is empirically validated using confirmatory factor analysis and structural equation model in the context of higher education institutions. A sample of 802 users comprising of engineering and management students has been used for the analysis.

Course attributes, system attributes, interactive attributes and instructor attributes were found to have an influence significantly on user satisfaction. Instructor attributes were the topmost significant contributor followed by the course attributes.

Delivery of educational programs through e-learning platforms has increasingly gained traction throughout the world owing to its locational, time and convenience-related facets. Further, the ongoing global pandemic has catalysed acceptance of e-learning platforms thus attracting large number of learners and teachers for facilitating the teaching-learning process. This paper is a novel attempt to identify the existing gaps in teaching-learning process in the context of e-learning.

This study is original and provides new insights into how e-learning platforms and higher education institutions can ensure higher user satisfaction and learning in current challenging times. This paper will also be of interest to policymakers.

The purpose of this paper is to formulate extended enterprise-oriented structure and process map for technical skill building for firms belonging to emerging economies.

The authors identify technical skill building (lies at the intersection of product, process and people) as a key enabler for furthering organizational competitiveness. The authors employ define measure explore develop implement- and supplier, input, process, output, and customer (SIPOC-) based framework for arriving at a technical skill building framework.

By utilizing the SIPOC-based framework, the authors identify the supplier(s), input(s), process(s), output(s) and customer(s) in the value chain of technical skill building as far as the extended enterprise is concerned.

The paper uses pragmatic and user-friendly conceptualization for technical skill building framework.

In this research, collaboration attributes related to the firm's intrinsic and extrinsic facets at pertinent levels (i.e. enterprise, strategic, operational, and tactical levels) for construction equipment OEMs (original equipment manufacturers) operating in India have been quantified and modeled.

For modeling the intra-firm collaboration at respective organizational levels, relevant attributes have been populated employing literature review followed by subsequent validation from pertinent focus groups. The focus groups comprising professionals working in the construction and mining equipment industry in India aided us in estimating the extent of interdependencies and influences within/amongst collaboration attributes. The collaboration attributes and respective interdependencies/influences are modeled employing the concept of graph theory wherein the individual attributes are represented using vertices and influences/interdependencies are represented using edges. The collaboration indices resulting from the variable permanent matrix have been derived as well.

Scenario and subsequent sensitivity analysis are performed. This research discusses the significance and aspects related to various collaborative attributes and the interrelations amongst them. Further, the research also evolves quantitative measures of collaboration indices at enterprise, strategic, tactical and operational levels by employing a graph-theoretic approach (GTA). The authors have also extricated and discussed a number of meaningful implications from both the perspectives of interorganizational relationships (IORs) and the normative theory of organizations using a cross-case analysis of five firms having operations in India.

The research would aid organizations (particularly those belonging to the construction equipment sector) measure the efficacy of collaboration in respective value-chains at strategic, tactical and operational levels. From the theoretical perspective, the integration of the IORs and normative theory of organizations enables looking at the intra-firm collaboration problem from a multi-dimensional standpoint involving activities, performance measures, action initiation, communication, shades of top management, level of activity, etc.

Sustainable supply chain (SSC) provides one opportunity to achieve competitive advantage. To achieve SSC through triple bottom line (TBL) – economic, environment and social – is extensively discussed. Most literature in dealing with environmental issues undermine social dimension even though its potential to bring outstanding results by earning customers loyalty and commitment is immense. Local orientation and different context motivate firms to prioritize sustainability dimensions differently. The purpose of this paper is to conceptualize SSC performance as three dimensional second-order formative construct which is caused by three first-order reflective constructs. Further, the authors examined effect of sustainable performance on barriers to sustainability through collaboration.

The model is validated by data collected from industries in India using both partial least squares and covariance based structural equation modeling. The authors find the model is valid for both manufacturing and service sectors.

In Indian context, social dimension is most and environmental dimension is least important differentiating it from developed economy. The authors find sustainable performance subsequently mitigates barriers and risks to sustainability, thereby reducing its impact over time.

This study conceptualizes SSC performance as three dimensional second-order formative construct which is caused by three first-order reflective constructs. Given criticisms to TBL for being western-centric, this study unearths insightful phenomena having implications for both developing and developed world. Further, the authors find sustainable performance reduces effects of barriers to collaboration necessary to achieve SSC. This study contributes to both theory and practice by modeling sustainability performance.

This paper analytically models and numerically investigates two operating levers, namely optimization of product price and optimization of product quality in the context of a manufacturer that sells the products directly in the marketplace. The study attempts to identify how optimizing product quality and product price can fulfill a manufacturer's economic aims such as maximization of the manufacturer's profit and market demand. Anchored to the extant literature, the demand is modeled as a parametric joint multiplicative function of price and quality. Further, price is modeled as a function of product quality.

First, the authors evolve the analytical expression for the manufacturer's profit. Thereafter, following the mathematical principles of unconstrained optimization, the authors arrive at the conditions for optimal product quality and product price. The authors further perform numerical experiments to understand the behavior of economic dimensions such as profit and demand with respect to sensitivities associated with cost, quality and price.

The authors find that under product quality optimization, the optimal product quality is a unique solution in that a highest possible theoretical manufacturer's profit is obtained. However, in the case of product price optimization, the optimal product price is non-unique and is a function of product quality. The authors further find that in the context of functional quality-level expectations, product quality optimization as an operating lever gives a better dividend. However, in the case of higher product quality expectations, product price optimization performs better than product quality optimization. Further, several novel findings are also obtained from numerical experimentations.

The findings of the authors' study have implications for types of industries characterized by relatively low as well as relatively high competitive intensity. Further, as opposed to several extant studies that have often carried out joint optimization of quality and price, the authors' study is one of the first to study the impact of product price and product quality on the manufacturer's economic objective in a disparate and focused manner, thus capturing individual effects.

An uncertain product demand in online retailing leads to loss of opportunity cost and customer dissatisfaction due to instances of product unavailability. On the other hand, when e-retailers store excessive inventory of durable goods to fulfill uncertain demand, it results in significant inventory holding and obsolescence cost. In view of such overstocking/understocking situations, this study attempts to mitigate online demand risk by exploring novel e-retailing approaches considering the trade-offs between opportunity cost/customer dissatisfaction and inventory holding/obsolescence cost.

Four e-retailing approaches are introduced to mitigate uncertain demand and minimize the economic losses to e-retailer. Using three months of purchased history data of online consumers for durable goods, four proposed approaches are tested by developing product attribute based algorithm to calculate the economic loss to the e-retailer.

Mixed e-retailing method of selling unavailable products from collaborative e-retail partner and alternative product's suggestion from own e-retailing method is found to be best for mitigating uncertain demand as well as limiting customer dissatisfaction.

Limited numbers of risk factor have been considered in this study. In the future, others risk factors like fraudulent order of high demand products, long delivery time window risk, damage and return risk of popular products can be incorporated and handled to reduce the economic loss.

The analysis can minimize the economic losses to an e-retailer and also can maximize the profit of collaborative e-retailing partner.

The study proposes a retailer to retailer collaboration approach without sharing the forecasted products' demand information.

Typically, the budgetary requirements for executing a supplier’s process quality improvement program are often done in unstructured ways in that quality improvement managers purely use their previous experiences and pertinent historical information. In this backdrop, the purpose of this paper is to ascertain the expected cost of carrying out suppliers’ process quality improvement programs that are driven by original equipment manufacturers (OEMs).

Using inputs from experts who had prior experience executing suppliers’ quality improvement programs and employing the Bayesian theory, transition probabilities to various quality levels from an initial quality level are ascertained. Thereafter, the Markov chain concept enables the authors to determine steady-state probabilities. These steady-state probabilities in conjunction with quality level cost coefficients yield the expected cost of quality improvement programs.

The novel method devised in this research is a key contribution of the work. Furthermore, various implications related to experts’ inputs, dynamics related to Markov chain, etc., are discussed. The method is illustrated using a real life of automotive industry in India.

The research contributes to the extant literature in that a new method of determining the expected cost of quality improvement is proposed. Furthermore, the method would be of value to OEMs and suppliers wherein the quality levels at a given time are the function of quality levels in preceding period(s).

The coronavirus (COVID-19) is the worst pandemic in recent memory in terms of its economic and social impacts. Deadly second wave of COVID-19 in India shook the country and reshaped the ways organizations functions and societies behave. Medical infrastructure was unaffordable and unsupportive which created high distress in the Indian society, especially for poor. At this juncture, some pharmaceutical firms made a unique social investment when they reduced price of drugs used to treat COVID-19 patients. This study aims to examine how the market and the society respond to the price reduction announcement during the psychological distress of COVID-19.

Market reactions have been analyzed by conducting an event study on stock market data and visual analytics-based sentiment analysis on Twitter data.

Overall, this study finds positive abnormal returns on the day and around the day of event. Interestingly, this study finds that returns during the time of high distress are significantly higher. Sentiment analysis conveys that net sentiment is favorable to the pharmaceutical firms around the day of event and it sustains more during the time of high distress.

This study is unique in contributing to the business and industrial management literature by highlighting market reactions to social responsibility of business during the time of psychological distress in emerging economies.

This research aims to aid product development managers to estimate the expected cost associated with the development of cost-intensive physical prototypes considering transitions associated with pertinent states of quality of the prototype and corresponding decision policies under the Markovian setting.

The authors evolve two types of optimization-based mathematical models under both deterministic and randomized policies. Under the deterministic policy, the product development managers take certain decisions such as “Do nothing,” “Overhaul,” or “Replace” corresponding to different quality states of prototype such as “Good as new,” “Functional with minor deterioration,” “Functional with major deterioration” and “Non-functional.” Under the randomized policy, the product development managers ascertain the probability distribution associated with these decisions corresponding to various states of quality. In both types of mathematical models, i.e. related to deterministic and randomized settings, minimization of the expected cost of the prototype remains the objective function.

Employing an illustrative case of the operator cabin from the construction equipment domain, the authors ascertain that randomized policy provides us with better decision interventions such that the expected cost of the prototype remains lower than that associated with the deterministic policy. The authors also ascertain the steady-state probabilities associated with a prototype remaining in a particular quality state. These findings have implications for product development budget, time to market, product quality, etc.

The authors’ work contributes toward the development of optimization-driven mathematical models that can encapsulate the nuances related to the uncertainty of transition of quality states of a prototype, decision policies at each quality state of the prototype while considering such facets for all constituent subsystems of the prototype. As opposed to a typical prescriptive study, their study captures the inherent uncertainties associated with states of quality in the context of prototype testing, etc.