Search results

The case deals with the Bullwhip phenomena that can be observed in a supply chain.

This case is suitable for all levels of students, undergraduate MBA to Executive MBA classes and practitioners. Assignment questions are designed from the perspective of teaching this case to a business student audience. The case is ideally suited for a supply chain management course and can be introduced to demonstrate the bullwhip effect in an operations management course.

Set in May 2011, the case presents the discussions in the meeting summoned by Mr Srinivas, the director (technical) of Health Pharma (not the name of a real organization) in response to the huge losses faced by the organization in the last financial year. The discussions point to the inability of the organization to appropriately forecast demand across the different echelons and also absence of information transparency, leading to the loss. The catastrophe indicated the need to adopt an ERP solution, which was earlier overlooked by Health Pharma management.

These are an introduction to the concepts of the bullwhip effect and the case presents a managerial solution to the supply chain problem demonstrated.

Teaching notes are available for facilitating the instructor to present and discuss the case in a classroom setting.

This paper aims to conceptualize and test an integrated model of online grocery buying intention by extending technology acceptance model by adding several antecedents of online grocery shopping behaviour such as physical effort, time pressure, entertainment value, product assortment, economic values, website design aesthetics, etc. The ultimate dependent variable was consumer’s satisfaction with buying process of grocery product via online platform.

The model was tested over online grocery shoppers using structural equation modelling approach. To enhance the validity of the finding, common method bias and social desirability bias were also assessed.

As product assortment was found to have a significant impact on both perceived ease of use and perceived usefulness, it supports the notion of one-stop solution as a major driver to attract buyers to buy groceries online. Findings also highlight the importance of entertainment value and economic value as key variables which shape the buyer’s satisfaction and purchase loyalty behaviour. Overall, the results support the proposed model.

The findings of this study would be helpful for online marketers to get more website visits and to increase conversion rates, i.e. getting their visitors to spend more time on the website and to make purchase.

This integrated framework tested here is quite comprehensive in nature, as it includes the influence of time pressure, physical effort and product assortment on online buying behaviour. These basic yet important variables to study, especially when the industry (online grocery shopping) is still in its nascent stage, are missing from the literature. The present study also involves a rigorous data analysis process followed by assessment of common method bias and psychometric property test. Such approach is rare in existing body of knowledge. The study uses S-O-R framework for hypothesis and model development, which is also rare in context of online grocery shopping.

Despite the current progress in realizing how Big Data Analytics can considerably enhance the Sustainable Manufacturing Supply Chain (SMSC), there is a major gap in the storyline relating factors of Big Data operations in managing information and trust among several operations of SMSC. This study attempts to fill this gap by studying the key enablers of using Big Data in SMSC operations obtained from the internet of Things (IoT) devices, group behavior parameters, social networks and ecosystem framework.

Adaptive Prospects (Improving SC performance, combating counterfeits, Productivity, Transparency, Security and Safety, Asset Management and Communication) are the constructs that this research first conceptualizes, defines and then evaluates in studying Big Data Analytics based operations in SMSC considering best worst method (BWM) technique.

To begin, two situations are explored one with Big Data Analytics and the other without are addressed using empirical studies. Second, Big Data deployment in addressing MSC barriers and synergistic role in achieving the goals of SMSC is analyzed. The study identifies lesser encounters of barriers and higher benefits of big data analytics in the SMSC scenario.

The research outcome revealed that to handle operations efficiently a 360-degree view of suppliers, distributors and logistics providers' information and trust is essential.

In the Post-COVID scenario, the supply chain practitioners may use the supply chain partner's data to develop resiliency and achieve sustainability.

The unique value that this study adds to the research is, it links the data, trust and sustainability aspects of the Manufacturing Supply Chain (MSC).

This paper aims to investigate hypothesized relationships between the Internet of things (IoT) and big data analytics (BDA) with supply chain visibility (SCV) and operational performance (OP) in the pharmaceutical manufacturing sector in Jordan. The paper also aims to test the conceptual model related to the indirect effects of SCV.

To achieve the objectives of this paper, a conceptual model was developed through a review of the current literature. Data analysis was performed by covariance-based structural equation modelling using Amos 25 software, and the convergent validity, discriminant validity, reliability and confirmatory factor analysis were verified. Then the hypotheses were tested.

The results of the study indicate that there is a positive and statistically significant relationship between the IoT and BDA on SCV and OP. The relationship was positive and statistically significant between SCV and OP. In addition, support for the mediation hypothesis that SCV mediates the relationship among IoT, BDA and OP was confirmed.

This paper provides new theoretical and managerial contributions that have not been covered in previous studies, and it is considered the first study that uses this conceptual model with this mechanism in terms of the theoretical lens and empirical application. This paper contributes to understanding the dynamic mechanisms of the IoT and BDA in enhancing OP, which contributes to creating a supply chain capable of facing various environmental fluctuations and pressures. This study presents new implications that can be used in the supply chain literature.