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The purpose of this paper is to empirically investigate linkage among productivity, quality, and business performance in home-based brassware units in India.

This study involved action research of home-based brassware units applying procedures for three-stage least-squares (3SLS) regression analysis, with data obtained through questionnaire survey based on convenience sampling.

This study has supported the established belief that quality leads to productivity, and subsequently productivity leads to better business performance for home-based brassware units in India. The consistent and logical result of this study using 3SLS regression analysis has provided empirical understanding of the appropriate linkage among productivity, quality, and business performance.

This study has limitations of findings, as it studied the home-based brassware units in the Indian context only.

This study implies that marketable home-based brassware products are to be produced by taking into account boundaries of production within the framework of goals and value created by motivation and dependability for monitoring the business performance. Identifying an appropriate linkage among productivity, quality, and business performance may project a holistic evaluation of the policy development related to home-based brassware units.

This is an original study to test empirical linkages among productivity, quality, and business performance using 3SLS regression analysis particularly for home-based brassware units in India.

To develop and examine an efficient and reliable jujube grading model with reduced computational time, which could be utilized in the food processing and packaging industries to perform quick grading and pricing of jujube as well as for the other similar types of fruits.

The whole process begins with manual analysis and collection of four jujube grades from the jujube tree, in addition to this jujube image acquisition was performed utilizing MVS which is further followed by image pre-processing and augmentation tasks. Eventually, classification models (i.e. proposed model, from scratch and pre-trained VGG16 and AlexNet) were trained and validated over the original and augmented datasets to discriminate the jujube into maturity grades.

The highest success rates reported over the original and augmented datasets were 97.53% (i.e. error of 2.47%) and 99.44% (i.e. error of 0.56%) respectively using Adam optimizer and a learning rate of 0.003.

The investigation relies upon a single view of the jujube image and the outer appearance of the jujube. In the future, multi-view image capturing system could be employed for the model training/validation.

Due to the vast functional derivatives of jujube, the identification of maturity grades of jujube is paramount in the fruit industry, functional food production industries and pharmaceutical industry. Therefore, the proposed model which is practically feasible and easy to implement could be utilized in such industries.

This research examines the performance of proposed CNN models for selected optimizer and learning rates for the grading of jujube maturity into four classes and compares them with the classical models to depict the sublime model in terms of accuracy, the number of parameters, epochs and computational time. After a thorough investigation of the models, it was discovered that the proposed model transcends both classical models in all aspects for both the original and augmented datasets utilizing Adam optimizer with learning rate of 0.003.

This study aims to examine a dual-pathway model that recognizes two distinct (formal and informal) but complementary mechanisms of knowledge exchanges – knowledge sharing and knowledge helping. It also investigates how team members use their limited human and psychosocial capital for prosocial knowledge effectiveness.

A survey-based approach was used to examine the hypotheses of the study. A moderated-mediation model was proposed and tested using bootstrap approach.

Knowledge sharing and knowledge helping were found to be the significant links through which human capital (capability) and psychosocial capital (motivation and efficacy) significantly predict prosocial knowledge effectiveness. Post hoc analysis suggests that human capital through knowledge sharing influences team learning, whereas the psychosocial capital through knowledge helping influences team leadership.

The present study found two distinct but complementary and yet necessary mechanisms of knowledge exchanges to be linked as the important outlay for the human and psychosocial capital to be effective in the prosocial knowledge behaviours.

The purpose of this paper is to explore the stock market impact of supply chain disruptions for public companies in Japan. The impact in the USA and Japan are also compared.

Using event study on a data set comprising of disruptions announced by Japanese and US companies during year 2000-2013, the authors measure the stock price reaction to supply chain disruptions.

The study finds that the Japanese companies, in an 11-day window around disruption announcement, witness an average abnormal return of −0.61 percent, which is statistically significant. In comparison to the USA, this stock decline is qualitatively smaller, yet statistically indifferent. The abnormal return is found significant in the two days before disruption announcement. However, a follow-up study with a refined data set (where the event date is the earlier of the announcement or disruption date) does not find any significant abnormal return prior to the event date. This difference from US market suggests the possibility of insider trading. Factors such as book-to-market ratio, industry type, and market capitalization did not affect the stock decline.

The research is limited to a data set from Japan and the USA. Further generalization of findings may need studies focused on other countries.

The results are of interest for supply chain managers. The results should also help global investors in making investment decisions.

Most supply chain disruptions management research is focused on companies in western countries. The paper is the first to test the impact of supply chain disruptions in Japan.

How psychological variables especially self-efficacy plays significant role to attain workplace well-being is yet to be explained. The extant literature calls for further research works in the field of sustainability practices to bridge the gap between self-efficacy and workplace well-being. The purpose of this paper is to extend the literature of workplace well-being while scientifically examining the moderating role of sustainability practices.

The study collected data from 527 full-time executives of Indian public and private manufacturing industries. The authors performed moderated regression analysis through a series of hierarchical models to test the hypotheses of the study.

The result indicates positive relationship between self-efficacy and workplace well-being. Furthermore, the result suggests that the relationship between self-efficacy and workplace well-being was stronger among executives with high level of sustainability practices and vice versa.

The cross-sectional sample of executives employed in Indian manufacturing organizations limits the generalizability of the findings.

HR functionaries and senior management may benefit by closely examining their sustainability practices along with their employees perceived ability to address workplace well-being.

The study contributes to extend the literature on self-efficacy and workplace well-being. This research work is one of the first few studies to examine the moderating effect of sustainability practices.