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The main objective in writing this paper and conducting this research is to enhance the productivity in manufacturing operations by making them cost effective.

This paper presents a target‐costing system and model developed for the turning operation and it has a user interface designed in Microsoft Visual Basic® with a database developed by using Microsoft Access®. An algorithm is developed to apply the concepts of target‐costing that selects the machining parameters and then determines the machining cost. A geometric programming model (Gopalakrishnan and Al‐Khayyal) was used in the development of this system.

The research determined that target‐costing models can be developed for the manufacturing industry and can be implemented in realistic manufacturing environment. The research also showcased the utility of the target‐costing model in terms of the underlying detailed system level parameters.

The research focuses on one manufacturing process but can be extended to other manufacturing processes and business cost and profit centers for providing overall and enhanced benefits at the corporate levels.

The research details the development of a model that has been validated using practical shop floor data, hence implying its application in a wide variety of situations.

The original value of the paper lies in identifying the critical parameters and modeling approach towards target‐costing.

The purpose of this paper is to investigate the effects of a commercial partnership in a project‐type supply chain. The research focuses on the performance of suppliers who develop a partnering mechanism for procurement of complex manufacturing projects. In total, four supply chain metrics are evaluated: project scope change, ratio of actual‐to‐estimated project costs, gross profit margin, and delay in deliverable shipments. Hypotheses are formulated to contrast partnerships and arms‐length relationships for industrial procurement. Statistical results support the conclusion that supplier performances improve under partnership.

Four supply chain metrics were generated through review of literature and in‐depth field study. The authors utilized the supply chain management, project management, and principal‐agent theory literature to develop hypotheses to examine effects of instituting a partnership agreement. A case study approach was employed to collect financial and operational data from 167 projects among a manufacturing supplier and a group of customers that purchase industrial analyzer systems. Statistical techniques were employed for hypothesis testing.

The findings from the authors' empirical work support the prediction in partnership literature that suppliers' operational and financial performances improve after they and manufacturing customers jointly implement partnerships. A supplementary finding also suggests that a manufacturer should develop partnering mechanisms with suppliers to achieve higher performance for both the individual firms and the entire supply chain.

This study, like other “before and after” analyses, encounters limitations on causality. Advanced techniques, e.g. cause‐effect investigation with richer data, are hence necessary to validate the causal relationships between performance metrics and their drivers. This study focuses only on the supplier's side of the supply chain and its partnership in a specific industrial setting. Future research may consider studying the joint performance by supplier‐customer dyads in commercial partnerships with variations of partnering agreements.

Partnerships motivate trading partners to engage in higher level of coordination. Transactional hazards can be reduced and performance may improve under the partnering mechanism. The manufacturer may design the procurement partnership as a collaborative mechanism, thus helping a partnering supplier and itself to obtain increased mutual gains.

The paper provides detailed information of a unique case study of the partnership in a project‐type supply chain, which is relatively new in the literature. Research streams on supply chain management, project management, and principal‐agent theory are integrated to evaluate supplier performance. Empirical results confirm partnership impacts on suppliers' business performance.

Sensemaking models generally lack an objective determinant to distinguish between CEO fault and changes in systematic risk caused by exogenous negative shocks like a banking crisis. The interdisciplinary approach of this paper combines attribution theory with econometric time series analyses to provide an objective measure of exogeneity and persistence of a negative shock to an organization. The purpose of this paper is to address the exploratory research question, of how scapegoating by managers can be avoided by the use of an objective and empirical measurement and if the recent financial crisis can be seen as an exogenous shock to manufacturing firms.

By testing for stationarity with a structural break with an econometric time series analysis, the model helps to reduce agency costs during organizational crisis by effectively determining crisis causation and avoid scapegoating by managers.

By combining the sensemaking models of Haleblian and Rajagopalan (2006), Staw (1980), and Weick (1988), an integrated model of sensemaking in performance crises under the specific context of simultaneously occurring external crises is provided. By applying the authors approach the results suggest that the financial crisis of 2008/2009 has true exogenous adverse effects on US manufacturing firms.

The interdisciplinary approach encourages the integration of econometric time series analysis as an objective determinant in sense making models.

The problem that original design manufacturing (ODM) companies encounter with the request for quotation (RFQ) process is that there is no effective and efficient methodology for them to formulate accurate and profitable RFQs. The purpose of this paper is to present a quality function deployment (QFD)‐, concurrent engineering (CE)‐, and target costing‐based methodology for ODM companies to formulate accurate and profitable RFQs.

From eight Taiwan electronics ODM companies, 15 people are interviewed to understand their current methods for formulating RFQs and the problems of these methods. Based on the interview results, it was decided to make use of the merits of QFD, CE, and target costing by integrating them into the proposed methodology.

A case study is presented to illustrate a successful application of the proposed methodology in a case company. The case study shows integrating QFD, CE, and target costing into the proposed methodology allows the authors to effectively and efficiently formulate an accurate and profitable RFQ for the case company.

The interview sample quantity of this study is limited to eight Taiwan electronics companies, which is insufficient to represent all ODM companies in various industries. For the future research, it is suggested researchers collect more samples from different industries in order to verify the effectiveness of the proposed methodology in ODM companies from different industries.

This paper aims to integrate QFD, CE, and target costing to come up with a systematic ten‐step approach that can accurately formulate the three parts of an RFQ: the product specifications proposal, the product price quotation, and the product development schedule. By adopting this methodology, ODM companies can provide accurate and profitable RFQs to ODM customers, thus increasing their chances of obtaining ODM business.

The purpose of this paper is to show how technical-economical cost modeling can help in steering research and development to target key production cost elements of new products based on emerging technologies.

The authors demonstrate the development and use of a technical-economic cost model (TCM) of the proton exchange membrane (PEM) in fuel cells to steer research to produce more economical and reliable products. A TCM is developed to depict how the production cost per unit varies depending on the different fabrication methods, production rate limitations, material selection, labor distribution, energy consumption, financial parameters and the target production volume. By using such an approach in the design, research time and resources can be saved by prioritizing R&D and production scale-up options at an early stage.

The results of this study show the importance of applying technical-economic cost model (TCM) techniques on early stage research projects to steer the development for resolving key problematic figures. As a case study, a cost analysis platform has been established to apply this technique by analyzing different manufacturing and R&D options for producing durable PEM fuel cells. The projected manufacturing cost of the PEM is found to be lower than previously estimated and the enhanced durability does not significantly impact this production cost.

Production is an important factor in informing NPD targets and R&D direction. And yet it is difficult to estimate scaled up production cost for prototype products and components in the R&D lab. Technical-economic cost models (TCM) are a tool to assist decision-making in technology portfolio management and NPD.

Small farmers in India are collectivized and legalized as Farmer Producer Companies (FPCs) to progress in agri-food value chains as small agribusiness enterprises. FPCs are dependent on timely information for their sustainability and profitability. Mobile apps are a cost-effective form of information and communication technology. Hence, the purpose of this study is to explore the major determinants of mobile apps adoption by FPCs.

Quantitative and qualitative data are collected by administering a semi-structured questionnaire and conducting in-depth interviews with board members of 115 FPCs, with a total membership of 30,405 farmers operating in 14 districts of the state of Kerala, India. The logit model is used for quantitative analysis, while dialog mapping is used for qualitative analysis, based on an integrated technology acceptance model and technology organization environment framework.

Logistic regression results evidence that amongst FPC characteristics, while company size and age are significantly impacting apps adoption, there is no significant association between board size, education level, multiple commodities business or export intention of companies on apps adoption. Digital literacy and technical hands-on training for FPC board members are quintessential to facilitate mobile apps adoption.

The findings are pertinent to policymakers to earmark funds for technical handholding and digital upskilling of FPCs. The need for developing comprehensive, location-centric, farmer-friendly apps by agritech companies is evidenced.

To the best of the authors’ knowledge, this is a pioneering work in the domain of mobile apps adoption from a farmers’ agribusiness enterprise perspective in an emerging market economy using a mixed-methods approach.

The study examines quick-commerce (Q-commerce) green initiatives' (GI') impact on consumer brand engagement by mediating [perceived value (PV) and environmental concern (EC)] and moderating (brand attitude).

The study gathered 458 surveys from recent Q-commerce shoppers, employing measurement and structural models alongside the PROCESS macro for data analysis.

The findings of the study indicate that (1) Q-commerce GI significantly affect PV, EC and directly impact customer brand engagement (CBE). The mediation analysis reveals that (2) PV positively influences EC and CBE; (3) EC has a favorable impact on CBE and (4) CBE positively affects brand attachment (Batta) and green-word of mouth (GWOM).

This study contributes to a deeper understanding of how Q-commerce's GI shape consumer brand engagement behavior. The insights provided can guide Q-commerce players and policymakers in the development and implementation of effective green practices.

The consumer-based study was conducted among the population of Kolkata metropolis to assess the impact of corporate social responsibility (CSR) practices on the purchase intention of selected cooking oil brands.

Data were collected from a questionnaire based survey on 322 respondents residing in Kolkata metropolis. Reliability of the scales was ascertained by Cronbach’s alpha values. Kendall's W test was used for rank analysis. Pearson’s correlation was examined to correlate the cognitive criteria. Factor analysis was used to sort out influential cognitive criteria which were compared between genders by the Kruskal–Wallis H test. The involvement of CSR components in enhancing the brand equity was analysed by multiple linear regression.

The brands vouching for the cause of health and nutritional value of the society attained significant loyalty and generate considerable brand association. The regression model predicts a socially accepted cooking oil brand to be one which addresses health, transparency and ethics in unison.

The study was restricted within the resident population of Kolkata metropolis which ratifies the CSR perception of a confined mass.

The study delineates the plausible avenue of CSR investments to touch the cognitive centre of the consumers’ mind.

The consumers expect to embrace a healthy yet reasonably priced cooking oil brand which imparts a notion to address multiple social causes.

The study identifies the strategic CSR attributes which might influence the mind of the consumers while they select cooking oil brands for household use.