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This paper introduces a Bayesian two-sided group chain sampling plan (BT-SGChSP) by using binomial distribution to estimate the average proportion of defectives. In this Bayesian approach, beta distribution is used as a suitable prior of binomial distribution. The proposed plan considers both consumer's and producer's risks. Currently, group chain sampling plans only consider the consumer's risk and do not account for the producer's risk. All existing plans are used to estimate only a single point, but this plan gives a quality region for the pre-specified values of different design parameters. In other words, instead of point wise description for the designing of sampling plan based on a range of quality by involving a novel approach called quality region.

The methodology is based on five phases, which are (1) operating procedure, (2) derivation of the probability of lot acceptance, (3) constructing plans for given acceptable quality level (AQL) and limiting quality level (LQL), (4) construction of quality intervals for BT-SGChSP and (5) selection of the sampling plans.

The findings show that the operating characteristic (OC) curve of BT-SGChSP is more ideal than the existing Bayesian group chain sampling plan because the quality regions for BT-SGChSP give less proportion of defectives for same consumer's and producer's risks.

There are four limitations in this study: first is the use of binomial distribution when deriving the probability of lot acceptance. Alternatively, it can be derived by using distributions such as Poisson, weighted Poisson and weighted binomial. The second is that beta distribution is used as prior distribution. Otherwise, different prior distributions can be used like: Rayleigh, exponential and generalized exponential. The third is that we adopt mean as a quality parameter, whereas median and other quintiles can be used. Forth, this paper considers probabilistic quality region (PQR) and indifference quality region (IQR).

The proposed plan is an alternative of traditional group chain sampling plans that are based on only current lot information. This plan considers current lot information with preceding and succeeding lot and also considers prior information of the product.

This paper first time uses a tight (three acceptance criteria) and introduces a BT-SGChSP to find quality regions for both producer's and consumer's risk.

This paper aims to provide a framework regarding Information Technology (IT) Flexibility in Supply Chain and its relationship with the benefits we could see from Enterprise Resource Planning (ERP) systems. Furthermore, this research explores the moderating effect of Process Integration Capability in the relationship between IT flexibility and ERP benefits.

This research model will help organizations get additional benefits from their ERP systems that incurred huge costs, time and multiple resources at their implementation. The technique used for analyzing data is structural equation modeling (SEM), and data is collected from 107 respondents through a questionnaire from Business and IT Professionals.

The study findings reveal a positive and significant relationship between IT flexibility and ERP systems benefits; moreover, results also confirmed that the organization's process integration capability significantly increased the benefits of ERP systems. The findings also highlight empirical evidence about the significance of the top-to-bottom approach investing in IT flexibility and the bottom-to-top approach during the implementation of IT systems for successful implementations.

This study has various implications for practitioners that help them successfully implement and long-term viability of their IT infrastructure.

This study's findings will help IT managers and strategists make effective decisions for creating IT flexibility in alignment with the strategic goals to realize the desired results expected from ERP systems and implementations of new IT systems.

The objective of this paper is to investigate the effect of supply chain quality integration (SCQI) and green supply chain practices and their impact on the Triple bottom line (TBL) in driving sustainability performance.

Structural equation modeling of partial least squares was used to study the relationships between SCQI and green supply chain practices (GSCPs) in driving sustainable performance and is empirically tested using data from 167 manufacturing firms.

This study reveals that supply chain quality integration (SCQI) enhances the green purchasing activity as well as the implementation of internal environmental management (IEM) of the firm. However, IEM is a crucial factor that contributes to sustainability performance.

This study is one of the few relevant researches that would benefit manufacturing organizations to further improve their triple bottom line by integrating supply chain quality with green practices.

Environmental performance (EnPerf) needs to be critically studied so organizations can understand enhancing it. The purpose of this study is mainly to examine and explain the influence of beliefs and values of the human resources regarding religiosity (REL) and workplace spirituality (WS) on shaping an environmentally friendly work culture comprising environmental ethics (EE) and environmental passion (EP), to enhance EnPerf.

A survey methodology was used, and 316 responses were collected from the employees working in industries on the top list of polluting the environment using purposive sampling. Structural equation modeling was deployed to test the hypotheses.

This research is conducted to identify specific relationships of variables with the environment. It was discovered that WS affected EP and EE, positively affecting EnPerf.

This study guides organizations and their management to adopt WS, EE and EP, as these all increase EnPerf in the organization.

Not much work has been conducted on the environmental culture based on REL and WS, using the ability-motivation-opportunity theory. This research analyzes employees’ intrinsic factors, such as REL and WS, to develop EP and EE. Thus helping to comprehend how they can use to enhance EnPerf, which is the current priority for the organizations.

The purpose of this study is to find the best geometries among the cylindrical, enamel and honeycomb geometries based upon the mechanical properties (tensile test, compression test and shear test). Further this obtained geometry could be used to fabricate products like exoskeleton and its supporting members.

The present research focuses on the mechanical testing of cylindrical, enamel and honeycomb-shaped parts fabricated through multi-jet printing (MJP) process with a wall thickness of 0.26, 0.33, 0.4 and 0.66 mm. The polymer specimens (for tensile, compression and shear tests) were fabricated using a multi-jet fusion process. The experimental results were compared with the numerical modelling. Finally, the optimal geometry was obtained, and the influence of wall thicknesses on various mechanical properties (tensile, compression and shear) was studied.

In comparison to cylindrical, enamel structures the honeycomb structures required less time to fabricate and had lower tensile, compressive and shear strengths. The most efficient geometry for fully functional parts where tensile, compressive and shear forces are present during application – cylindrical geometry is preferred followed by enamel, and then honeycomb. It was found that as the wall thickness of various geometries was increased, their ability to withstand tensile, compressive and shear loads also enhanced. The enamel shape structure exhibits greater strain energy storage capacity than other shape structures for compressive loads, and the strength to resist the compressive load will be lower. In the case of cylindrical geometries for tensile loading, the resisting area toward the loading will be higher in comparison to honeycomb- and enamel-based structures. At the same time, the ability to store the stain energy is less. The results of the tensile, compression and shear load finite element analysis using ANSYS are in agreement with those of the experiments.

From the insight of literature review, it is found that a wide range of work is done on fused deposition modeling (FDM) process. But in comparison to FDM, the MJP provide the better dimensional accuracy and surface properties (Lee et al., 2020). Therefore, it is observed that past research works not incorporated the effect of wall thickness of the embedded geometries on mechanical properties of the part fabricated on MJP (Gibson, n.d.). Hence, in this work, effect of wall thickness on tensile, compression and shear strength is considered as the main factor for the honeycomb, enamel and cylindrical geometries.

This paper assesses the environment of legitimacy by determining the role of institutional quality and policy uncertainty on the performance of five major South Asian stock markets (India, Pakistan, Bangladesh, Sri Lanka, and Nepal) using 21 years data from 2000 to 2020. The focus of this study is to approach the issue of the environment of legitimacy that leads to sustained market returns.

Panel cointegration tests of Kao and Pedroni are applied, and the Dynamic Panel Vector Autoregressive (PVAR) model is used to determine the estimates.

ADF P-Values of both Kao and Pedroni tests show that the panels are cointegrated; the statistical significance of the results of the Kao and Pedroni panel cointegration test confirms cointegration among the variables. After determining the most appropriate lag, the analysis is done using PVAR. The results indicate that institutional quality, policy uncertainty, and GDP positively affect stock market return. Meanwhile, government actions and inflation negatively affect stock market returns. On the other hand, stock market return positively affects institutional quality, government action, policy uncertainty, and GDP. While stock market return negatively affects inflation.

The sample is taken only from a limited number of South Asian countries, and the period is also limited to 21 years.

Based on our research findings, we have identified several policy implications recommended to enhance and sustain the performance of stock markets.

This paper uses a unique analytical tool, which gives a better insight into the problem. The value of this work lies in its findings, which also have practical implications and theoretical significance.